Capso: A Multi-Objective Cultural Algorithm System To Predict Locations Of Ancient Sites

ABSTRACT CAPSO: A MULTI-OBJECTIVE CULTURAL ALGORITHM SYSTEM TO PREDICT LOCATIONS OF ANCIENT SITES by SAMUEL DUSTIN STANLEY August 2019 Advisor: Dr. Robert Reynolds Major: Computer Science Degree: Doctor of Philosophy The recent archaeological discovery by Dr. John O’Shea at University of Michigan of prehistoric caribou remains and Paleo-Indian structures underneath the Great Lakes has opened up an opportunity for Computer Scientists to develop dynamic systems modelling these ancient caribou routes and hunter-gatherer settlement systems as well as the prehistoric environments that they existed in. The Wayne State University Cultural Algorithm team has been interested assisting Dr. O’Shea’s archaeological team by predicting new structures in the Alpena-Amberley Ridge Region. To further this end, we developed a rule-based expert prediction system to work with our team’s dynamic model of the Paleolithic environment. In order to evolve the rules and thresholds within this expert system, we developed a Pareto-based multi-objective optimizer called CAPSO, which stands for Cultural Algorithm Particle Swarm Optimizer. CAPSO is fully parallelized and is able to work with modern multicore CPU architecture, which enables CAPSO to handle “big data” problems such as this one. The crux of our methodology is to set up a biobjective problem with the objectives being locations predicted by the expert system (minimize) vs. training set occupational structures within those predicted locations (maximize). The first of these quantities plays the role of “cost” while the second plays the role of “benefit”. Four separate such biobjective problems are created, one for each of the four relevant occupational structure types (hunting blinds, drive lines, caches, and logistical camps). For each of these problems, when CAPSO tunes the system’s rules and thresholds, it changes which locations are predicted and hence also which structures are flagged. By repeatedly tuning the rules and thresholds, CAPSO creates a Pareto Front of locations predicted vs. structures predicted for each of the four occupational structure types. Statistical analysis of these Pareto Fronts reveals that as the number of structures predicted (benefit) increases linearly, the number of locations predicted (cost) increases exponentially. This pattern is referred to in the dissertation as the Accelerating Cost Hypothesis (ACH). The ACH statistically holds for all four structure types, and is the result of imperfect information

Analyzing Environmental Change And Prehistoric Hunter Behavior Through A 3d Time-Lapsed Model With Level Auto-Generation And Cultural Algorithms

This paper describes a system containing two portions whose purpose it is to help further the Alpena-Amberley Land Bridge research project and similar archaeological research. The first portion is a time engine which one can utilize to navigate through time in order to see how environmental conditions evolved as time passed, or to run experiments during a desired time period. The second portion is a hunting blind cultural algorithm, which is built on top of the time engine as well as Palazzolo\u27s program. In this portion, the AI hunting blinds react to the goals that they are trying to achieve, and the goals themselves change as the environment changes over time. When the cultural algorithm is finished, the system also produces a frequency heatmap showing how often the system predicted a hunting blind within each location throughout the entire time period. Archaeologists can use this to determine which places in the area would be most worthy of sending an expedition

The Mediating Effect of Firm Characteristics on the Relationship Between Green Marketing and Sustainability Performance: A Critical Review of the Literature and Research Agenda

Firms are beginning to determine how the adoption of green marketing can benefit or harm their sustainability performance. The application of green marketing which implies numerous changes in approach, which primarily relate to the modification of the basic elements of the marketing mix have taken strategic importance. This study paper aims to conceptualize and examine the empirical literature, theoretical and methodological gaps and propose conceptual framework for implementation of relationship between green marketing and sustainability performance. The theories underpinning the study are; Social Marketing theory, stakeholder’s theory and agency theory. The study proposes positivism philosophy as the most suitable philosophy in a bid to quantify the relationship between the constructs under the study. Descriptive research design will be used. Semi structured questionnaire will be used for data collection. Multiple linear regression model will be used for data analysis. Factor analysis will also be employed for testing indicators of green marketing and sustainability performance. Both descriptive and inferential statistics will be proposed for data analysis. Though the study was conducted on green marketing and sustainability performance, similar studies should be conducted on other variables apart from the ones discussed to show their relationship and also include various contextual aspects. Further studies should also consider other mediating and moderating variables apart from the ones proposed under this study Keywords: Green marketing, sustainability performance and firm characteristics DOI: 10.7176/EJBM/12-36-09 Publication date: December 31st 2020

PRODUCER ACCEPTANCE OF A NEW PEANUT MARKETING COOPERATIVE: A SURVEY OF GEORGIA PEANUT PRODUCERS

Market conduct has become an important issue for peanut farmers. Consolidation in the first buyer market, increased imports, and political uncertainty have increased peanut producers' marketing risks. The purpose of this paper was to examine demographic differences in peanut producers' perceptions of the current marketing environment as well as their attitudes towards new marketing institutions. A standard t-test revealed that producers growing more than 250 acres of peanuts, irrigating at least 50 percent of their peanuts, and producers located in Southwest Georgia were statistically more dissatisfied with the current marketing environment and significantly more receptive to forming a new generation peanut cooperative.Agribusiness, Crop Production/Industries,

A NEW GENERATION PEANUT COOPERATIVE IN GEORGIA: A BENEFIT-COST ANALYSIS

A survey of Georgia peanut producers revealed that the Southwest corner of Georgia could be targeted for a new generation peanut cooperative (FS 01-07). The objective of this study was to examine the feasibility of this option. Preliminary results revealed that this might be an economically feasible solution to peanut producers' marketing problems. The projected discounted benefit-cost ratios ranged from 1.9 to 1.4 over a ten-year period.Agribusiness, Crop Production/Industries,

UPI: A Primary Index for Uncertain Databases

Uncertain data management has received growing attention from industry and academia. Many efforts have been made to optimize uncertain databases, including the development of special index data structures. However, none of these efforts have explored primary (clustered) indexes for uncertain databases, despite the fact that clustering has the potential to offer substantial speedups for non-selective analytic queries on large uncertain databases. In this paper, we propose a new index called a UPI (Uncertain Primary Index) that clusters heap files according to uncertain attributes with both discrete and continuous uncertainty distributions. Because uncertain attributes may have several possible values, a UPI on an uncertain attribute duplicates tuple data once for each possible value. To prevent the size of the UPI from becoming unmanageable, its size is kept small by placing low-probability tuples in a special Cutoff Index that is consulted only when queries for low-probability values are run. We also propose several other optimizations, including techniques to improve secondary index performance and techniques to reduce maintenance costs and fragmentation by buffering changes to the table and writing updates in sequential batches. Finally, we develop cost models for UPIs to estimate query performance in various settings to help automatically select tuning parameters of a UPI. We have implemented a prototype UPI and experimented on two real datasets. Our results show that UPIs can significantly (up to two orders of magnitude) improve the performance of uncertain queries both over clustered and unclustered attributes. We also show that our buffering techniques mitigate table fragmentation and keep the maintenance cost as low as or even lower than using an unclustered heap file.National Science Foundation (U.S.) (Grant IIS-0448124)National Science Foundation (U.S.) (Grant IIS-0905553)National Science Foundation (U.S.) (Grant IIS-0916691

Personal Health Records: Beneficial or Burdensome for Patients and Healthcare Providers?

Personal health records (PHRs) have been mandated to be made available to patients to provide increased access to medical care information, encourage participation in healthcare decision making, and enable correction of errors within medical records. The purpose of this study was to analyze the usefulness of PHRs from the perspectives of patients and providers. The methodology of this qualitative study was a literature review using 34 articles. PHRs are powerful tools for patients and healthcare providers. Better healthcare results and correction of medical records have been shown to be positive outcomes of the use of PHRs. PHRs have also been shown to be difficult for patients to use and understand, and providers had concerns about correct information transferring to the portals and patients eliminating information from the record. Concerns regarding patient understanding of medical records, legal liability, and the response time required of providers were also identified. For the PHR to succeed in the US healthcare system, assurance that the information will be protected, useful, and easily accessed is necessary

Clinical perspectives of emerging pathogens in bleeding disorders.

As a result of immunological and nucleic-acid screening of plasma donations for transfusion-transmissible viruses, and the incorporation of viral reduction processes during plasma fractionation, coagulation-factor concentrates (CFC) are now judged safe in terms of many known infectious agents, including hepatitis B and C viruses, HIV, and human T-cell lymphotropic virus. However, emerging pathogens could pose future threats, particularly those with blood-borne stages that are resistant to viral-inactivation steps in the manufacturing process, such as non-lipid-coated viruses. As outlined in this Review, better understanding of infectious diseases allows challenges from newly described agents of potential concern in the future to be anticipated, but the processes of zoonotic transmission and genetic selection or modification ensure that plasma-derived products will continue to be subject to infectious concerns. Manufacturers of plasma-derived CFC have addressed the issue of emerging infectious agents by developing recombinant products that limit the need for human plasma during production. Such recombinant products have extended the safety profile of their predecessors by ensuring that all reagents used for cell culture, purification steps, and stabilisation and storage buffers are completely independent of human plasma