Knowledge Of Metrics Research Articles

Quantifying Knowledgeof Metrics and Measures in Modern Library Science

The content of this study attempts to get the role of measurement within contemporary library science and will deliver a comprehensive analysis on how performance and services are affected to the maximum in our country ́s library systems. The research includes all manner of libraries, including universities, public libraries, special libraries, etc., and makes use of both quantitative and qualitative research methods for the purposes. The chief subject of study will include the historical development of library science; how the metrics currently employed have been interpreted; as well as the problems and opportunities that accompany present efforts to appraise the impact of library services. This research includes cases of successful metrics-driven change which analyze the impact of information literacy initiatives and evaluates the effect of outreach programs. This research project also treats the future of library science through the discovery. These results speak to the fluid character of digital-age library services, while suggesting that innovative techniques seam to be a necessity for adaptation and even growth of any durability in the new environment

Upgrading and inequality in global value chains: Challenges for inclusive and sustainable development

The phenomena of globalization and fragmentation of production drive countries to face a double challenge of catching up: economic upgrading coupled with improvement in living standards. Meanwhile, insertion and upgrading within global value chains (GVCs) deeply affect national economies in multiple ways. In this paper, we explore the research agenda on the distributional outcomes of the integration of countries into GVCs, with special attention paid to developing countries. A critical review of both the existing literature on the relationship between economic and social upgrading and the methodological approaches to GVC integration and their distributional outcomes are undertaken, in order to improve understanding and to help orient policy strategies. We highlight the relevance of institutions as well as the role of governments and MNE initiatives to ensure that the achievement of sustainable economic gains are translated into social benefits. This can be attained by the reinforcement of welfare and labour institutions, the strengthening of innovation systems, and support for and densification of local chains. There is a pressing need for further research on this topic founded on accurate knowledge of metrics and indicators for analyzing the insertion of countries into GVCs as well as their distributive outcomes.

A New Typology Design of Performance Metrics to Measure Errors in Machine Learning Regression Algorithms

Aim/Purpose: The aim of this study was to analyze various performance metrics and approaches to their classification. The main goal of the study was to develop a new typology that will help to advance knowledge of metrics and facilitate their use in machine learning regression algorithms Background: Performance metrics (error measures) are vital components of the evaluation frameworks in various fields. A performance metric can be defined as a logical and mathematical construct designed to measure how close are the actual results from what has been expected or predicted. A vast variety of performance metrics have been described in academic literature. The most commonly mentioned metrics in research studies are Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), etc. Knowledge about metrics properties needs to be systematized to simplify the design and use of the metrics. Methodology: A qualitative study was conducted to achieve the objectives of identifying related peer-reviewed research studies, literature reviews, critical thinking and inductive reasoning. Contribution: The main contribution of this paper is in ordering knowledge of performance metrics and enhancing understanding of their structure and properties by proposing a new typology, generic primary metrics mathematical formula and a visualization chart Findings: Based on the analysis of the structure of numerous performance metrics, we proposed a framework of metrics which includes four (4) categories: primary metrics, extended metrics, composite metrics, and hybrid sets of metrics. The paper identified three (3) key components (dimensions) that determine the structure and properties of primary metrics: method of determining point distance, method of normalization, method of aggregation of point distances over a data set. For each component, implementation options have been identified. The suggested new typology has been shown to cover a total of over 40 commonly used primary metrics Recommendations for Practitioners: Presented findings can be used to facilitate teaching performance metrics to university students and expedite metrics selection and implementation processes for practitioners Recommendation for Researchers: By using the proposed typology, researchers can streamline development of new metrics with predetermined properties Impact on Society: The outcomes of this study could be used for improving evaluation results in machine learning regression, forecasting and prognostics with direct or indirect positive impacts on innovation and productivity in a societal sense Future Research: Future research is needed to examine the properties of the extended metrics, composite metrics, and hybrid sets of metrics. Empirical study of the metrics is needed using R Studio or Azure Machine Learning Studio, to find associations between the properties of primary metrics and their “numerical” behavior in a wide spectrum of data characteristics and business or research requirements

A Knowledge of Metrics on Analysis of Social Graphs

Graph based data mining has become quite popular in the last few years. One of the best studied data structures in computer science and discrete mathematics are graphs. The use of social media has grown significantly in recent years. With the growth in its use, there has also been a substantial growth in the amount of information generated by users of social media. This paper discusses the metrics which are used in mining of social graphs. Keywords: Data Mining, Graphs, Social Graphs

A Knowledge of Metrics on Analysis of Social Graphs

Graph based data mining has become quite popular in the last few years. One of the best studied data structures in computer science and discrete mathematics are graphs. The use of social media has grown significantly in recent years. With the growth in its use, there has also been a substantial growth in the amount of information generated by users of social media. This paper discusses the metrics which are used in mining of social graphs.

Metric Knowledge and Awareness of College Students in Basic Foods and Nutrition Courses

LEARNING OUTCOME: To identify the extent of knowledge and awareness of metrics by college students in basic foods and nutrition courses and implications for teaching and using metric (SI) units in these and other foods and nutrition classes. Metrication is progressing in the United States and the metric terminology used in classes can affect the level of students’ understanding of course content on topics such as nutrition labeling, food container sizes, recommended dietary allowances, and body mass index. Thus, the extent of knowledge of metric (SI) units was assessed in three introductory foods and nutrition classes on the first class session in January 1997. A total of 208 students completed the brief survey which assessed knowledge of terms used for mass, volume, distance, and temperature, and ability to utilize metric prefixes and metric equivalents for units expressed in U.S. household measures. Also assessed was awareness by students of where they encounter metrics in their everyday lives. Descriptive statistics of the data were computed using SPSS. Students were uniformly able to identify the metric terms associated with mass, volume, distance and temperature, while fewer than half were able to correctly indicate the portion or multiple of a meter represented by as many as two of the four given prefixes. The mean number of correct responses was 1.4 out of 4.0. Conversion from U.S. household measures to metric-equivalent units was correctly made by no more than 10 percent of the respondents on any one of the four examples, with a mean correct score of 0.1 out of a potential 4.0. Awareness of metrics in everyday settings was limited, with an average of only 1.0 settings mentioned. Most frequently identified places, in decreasing order of mention, were product labels, academic classes, and in cooking. As educators we assume that students are knowledgeable of the terms we use. However, if these study subjects are typical of current college students we will need to teach, or at least review thoroughly, metric prefixes and conversions in order to adequately equip students to comprehend and apply the concepts we teach and ultimately to use them in their professions as the U.S. moves to adopt metrics.