A technical review of no-reference image quality assessment algorithms for contrast distorted images

Automatic image quality assessment similar to human vision perception is an essential process for real-time image processing applications to perform perceptual image assessments for effectively achieving their goals. As no-reference image quality assessment (NR-IQA) schemes perform perceptual assessments of images without any information about their original version, these algorithms suit real-time computer vision techniques because of the non-availability of reference images. Contrast and colorfulness play important roles in determining the quality of color images. By combining many IQA metrics, a number of combined metrics had been devised. This study provides an insight into major NR-IQA methods and their effectiveness in assessing contrast, colorfulness, and overall quality of contrast-degraded images with technical analysis. The effectiveness of top-ranking NR-IQA methods is experimentally assessed with benchmark assessment methods on images from benchmarked databases. The study provides insight into open research challenges in the area of NR-IQA for developing new promising methods by clearly demarcating the difficulties of top-ranking NR-IQA methods.

Application of Data Mining in Traditional Benchmark Evaluation Model for Buildings Energy Consumption

Since the beginning of data mining technologies, buildings have become not just energy-intensive but also information-centric. Data mining technologies have been widely used to utilize the huge quantities of buildings’ operational data to improve their energy systems. Conventional benchmarking of buildings’ energy performance reflects a variety of parameters, such as the number of inhabitants, the environment, the energy efficiency of equipment utilized, and the adjustment of internal temperature. These various elements are then assigned weights to generate a single general indicator. This study presents a reasonable benchmark assessment methodology of conventional buildings’ energy usage based on a data-mining algorithm for acquiring more specific information, like the energy management efficacy of a building, and aiming at the problem of ineffective use of large amounts of energy consumption in public buildings. A mathematical-statistical approach and a data-mining tool are used to analyse the data. The degree of connection between numerous influencing variables (i.e., characteristic parameters) and building’s energy usage is determined using grey correlation analysis. In this work, we have used an enhanced Apriori algorithm to identify the link between the different forms of systems in the same area. In short, the fundamental idea and process of the Apriori algorithm are presented, and preliminary designs of the preprocessing of experimental data as well as the analysis methods are studied to analyse the outcome of the proposed work.

How Benchmark Is Used in Third Grade Reading Instruction

Third grade reading teachers at the local setting are not consistently using formative benchmark data to improve student reading performance, creating a gap in practice. This gap in practice may be due to teachers’ lack of capacity to use the data to make changes to their instructional practices. The purpose of this qualitative study was to explore how third grade reading teachers are using data from reading benchmark assessments to improve student reading performance. This research study was guided by two Research Questions (RQs). RQ 1 addressed how third grade teachers are using reading benchmark assessment data to improve student reading performance. RQ 2 addressed specific instructional strategies that third grade teachers are using from reading benchmark assessment data to effectively improve student reading performance. Data-driven decision making (DDDM) was the conceptual framework that was the foundation for this study. This basic qualitative design for this research study included 13 participants. Data were collected through open-ended semistructured interviews, and qualitative analyses were conducted through open coding and thematic analysis. According to the findings of this study, immediately analyzing data, collaboration, and data driven instruction were the themes that emerged guided by RQ 1. Emerging themes for RQ 2 included test taking strategies, modeling, and guided reading. Leadership in this district may use these findings to make decisions about the effectiveness of teachers’ use of these benchmark assessments or the data gathered from the assessments to impact student reading proficiencies. This research may provide specific instructional strategies used through the DDDM process that increases student reading proficiency. The findings could possibly yield results that have positive social change implications for reading achievement.

Effective Programs in Elementary Mathematics: A Meta-Analysis

This article reviews research on the achievement outcomes of elementary mathematics programs; 87 rigorous experimental studies evaluated 66 programs in grades K–5. Programs were organized in six categories. Particularly positive outcomes were found for tutoring programs (effect size [ES] = +0.20, k = 22). Positive outcomes were also seen in studies focused on professional development for classroom organization and management (e.g., cooperative learning; ES = +0.19, k = 7). Professional development approaches focused on helping teachers gain in understanding of mathematics content and pedagogy had little impact on student achievement. Professional development intended to help in the adoption of new curricula had a small but significant impact for traditional (nondigital) curricula (ES = +0.12, k = 7), but not for digital curricula. Traditional and digital curricula with limited professional development, as well as benchmark assessment programs, found few positive effects.

Benchmark assessment of molecular geometries and energies from small molecule force fields

Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.

Community-Based Social Marketing in Theory and Practice: Five Case Studies of Water Efficiency Programs in Canada

Background: Community-based social marketing (CBSM) offers a pragmatic five-step approach to developing a program that fosters sustainable behaviour. However, how the CBSM theoretical framework has been implemented into practice remains largely under-evaluated. To help address this gap, Lynes et al. developed 21 benchmarks to assess CBSM programs. This research builds upon these benchmarks by using both the benchmarks and additional assessment criteria to assess five Canadian programs that have used CBSM principles. Focus: This paper is related to research and evaluation of community-based social marketing. Research Question: How has the CBSM theoretical framework been implemented in practice at the community level? Importance to the Social Marketing Field: By exploring how five Canadian programs have implemented CBSM, this paper enables practitioners to align their programs with CBSM principles more closely. It also contributes to the literature on CBSM effectiveness. Methods: Five qualitative case studies were assessed, each featuring a Canadian community program seeking to influence residential water efficiency behaviour. In order to systematically assess each program’s adherence to the CBSM theoretical framework, a CBSM benchmark assessment tool that proposes additional assessment criteria to Lynes et al.’s 21 benchmarks was developed. The assessment tool allowed for replicable benchmark assessments across multiple programs. Triangulation of data from both primary (survey and interview) and secondary (peer-reviewed literature, gray literature, and online reporting) data sources informed the assessment of each case study. Results: On average, over the five case studies, just over half of the 21 benchmark criteria were fully integrated into the programs, whereas just under a third were partially integrated, and approximately one fifth were not integrated at all. Recommendations for Research or Practice: While the benchmarks were fairly well integrated overall, this paper outlines several recommendations that programs may consider to improve alignment with the CBSM theoretical framework and benchmarks. Recommendations for future research to explore CBSM effectiveness are also made. Limitations: Lack of generalizability due to small sample size, unable to make assessments of programmatic success, and inherent limitations of the benchmark assessment tool.