Fully Automated Sunspot Detection and Classification Using SDO HMI Imagery in MATLAB

An automatic sunspot detection and classification method is developed combining HMII and HMIM imagery procured from the Solar Dynamics Observatory. Iterative global thresholding methods are employed for detecting sunspots. Groups are selected based on heliographic distance between sunspots via area-based grouping lengths. Classifications are applied through logical operators adhering to the standard McIntosh classification system. Calculated sunspot parameters and classifications are validated in three way comparisons between code output, Holloman AFB and the Space Weather Prediction Center. Accuracy is achieved within the margin of difference between Holloman and SWPC reports for sunspot area, number of groups, number of spots, and McIntosh classification using data spanning 6 July 2012 to 29 June 2013: SWPC/Holloman (33.38%,57.48%,87.67%), SWPC/SDO (20.22%,51.25%,83.80%), and SDO/Holloman (24.54%,50.91%,80.65%). The automatic classification system is used to evaluate bias inherent in Holloman classification methods. Parameters are altered to reach optimal match percentages with Holloman, indicating differences between computed parameter values and hand-calculated counterparts. Group length cutoffs are shown to differ by 2.5°, eccentricity is quantified at 0.8, and penumbra length cutoffs are shown to exceed differences of 1.4° from McIntosh values

Factors associated with physical activity participation in adults with chronic cervical spine pain: a systematic review

Objective: To determine the factors associated with physical activity participation in adults with chronic cervical spine pain. Methods: A systematic review was conducted including searches of PubMed (MEDLINE), EMBASE and CINAHL from inception to June 12th, 2016. Grey literature and reference checking was also undertaken. Quantitative studies including factors related to physical activity participation in adults with chronic cervical spine pain were included. Two independent authors conducted the searches, extracted data and completed methodological quality assessment. Results: A total of seven studies met the selection criteria, however, four papers were finally included in the final review. A modified Downs and Black criteria was used to assess methodological quality, each study included was classed as moderate quality. A total of six factors were assessed against physical activity participation for people with chronic neck pain. These included: pain, fear of movement, smoking habits, socioeconomic status, gender, leisure and work time habits. A significant relationship was demonstrated between pain, leisure and work time habits and physical activity. Subjects were less likely to participate in physical activity if they were in pain. Subjects with neck pain were less likely to participate in physical activity in their leisure and work time. Conclusion: This review, based on a small number of heterogeneous studies demonstrated key factors that are likely to affect physical activity in people with chronic neck pain, most notably, pain levels, leisure and work habits. This review suggests that more in-depth, high quality studies are required to fully understand the impact of chronic pain on physical activity

Impact of Ranch and Market Factors on an Index of Agricultural Holding Period Returns

This study develops nominal and real holding period return indices for operating ranches. The indices contain two components, monthly ranch operating profit and capital appreciation. A regression model that determines the effect of various attributes on total market value is used to estimate capital appreciation, and a second model determines operating profit. The two different ranch data series are compared with United States Long Term Government Bonds, the S&P 500 Index and Small Capitalization Stocks. Both ranch indices show very low correlation with the S&P 500 Index and very low or negative betas. Further, both ranch series have excess actual nominal and real returns when compared to expected returns determined from the Capital Asset Pricing Model.

Using multiple criteria decision analysis (MCDA) to assist in estimating residential housing values

Considerable literature exists regarding the complexity of the residential real estate appraisal process and the methods employed to determine initial listing prices as estimates of intrinsic market prices. Deviations in residential real estate intrinsic values occur due to a multiplicity of attributes and explanatory factors requiring consideration. We conduct a panel study using a Multiple Criteria Decision Analysis (MCDA) based framework that utilizes the skills and knowledge of a panel of residential real estate professionals (i.e. appraisers and realtors). We demonstrate how cognitive mapping and the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) may assist in estimating appropriate offer/sale prices and strengthening current valuation approaches such as using comparables and/or hedonic modeling. The managerial implications of our MCDA-based framework and some avenues for future research are also presented.info:eu-repo/semantics/publishedVersio

A rule-based decision support system for real estate brokerage service evaluation

Real estate brokers or realtors are expected to possess superior knowledge of their local markets, and typically require commissions in return for their services. The evaluation of their performance is an important issue in justifying their commissions. We develop a learning-oriented decision-making process for evaluating real estate brokerage services, which concentrates on understanding the nature, the role and the interaction of the evaluation aspects of real estate brokerage service quality by integrating cognitive maps and the Decision EXpert (DEX) approach. Results suggest that this framework permits new rudiments to be considered in the realtor decision-making and sales process, facilitating transparency and understanding of realtor functions that may lead to recommendations to improve the performance and quality of these functions. Avenues for future research are also presented.info:eu-repo/semantics/publishedVersio

How to create indices for bank branch financial performance measurement using MCDA techniques: an illustrative example

Most banks have been negatively affected by the recent economic recession, which has forced them to evaluate their operating performance including the financial performance of bank branches. Approaches that have been applied to address the financial performance evaluation of bank branches include: optimization techniques, simulations, stochastic tools, fuzzy logics and decision support systems. Although recent improvements have been made in assessing financial performance, the potential for significant further improvement remains since the recent world economic crisis is adding pressure on business margins. The purpose of this paper is to construct an exemplificative evaluation index for bank branch financial performance by integrating cognitive maps with measuring attractiveness by a categorical based evaluation technique. We aim to apply this methodology constructively to serve as a learning mechanism and introduce transparency in the decision making process. Practical applications, strengths and weaknesses of the proposed evaluation index are also discussed

Factors influencing physical activity participation in adults with chronic cervical spine pain

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