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data collection and analysis for preschoolers: An engaging context for integrating mathematics and computational thinking with digital tools

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EARLY CHILDHOOD RESEARCH QUARTERLY 2023年 65卷 42-56页

作者： Presser, Ashley E. Lewis Young, Jessica Mercer Rosenfeld, Deborah Clements, Lindsay J. Kook, Janna F. Sherwood, Heather Cerrone, Michelle Educ Dev Ctr 96 Morton St7th Floor New York NY 10014 USA

Collecting and organizing data to understand and answer real-world questions is an increasingly important skill in our current world. Fostering data collection and analysis (DCA) skills in young children leverages key mathematics skills as well as the data representation, visualization, and interpretation skills of computational thinking (CT), culminating in a problem-solving approach with data. As such, the intervention, comprising investigations and a digital app, supported preschool teachers and children to answer data-focused questions by engaging in each step of the DCA process in order to foster CT and math skills. Teachers appreciated that the app offers a new way for children to visualize data and noted that the app provided learning opportunities for children that would not otherwise be possible or easy to implement. Results also suggest that the app provides a systematic process for data collection, entry, and interpretation. Children in classrooms that completed the intervention had significantly higher scores at post-intervention compared to children in classrooms that did not complete the intervention, controlling for pre-intervention scores, B(SE) = 0.13(0.05), t (6) = 2.48, p = .048.

关键词： Preschool Mathematics data collection and analysis Computational thinking Technology

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Local Differential Privacy for data collection and analysis

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NEUROCOMPUTING 2021年 426卷 114-133页

作者： Wang, Teng Zhao, Jun Hu, Zhi Yang, Xinyu Ren, Xuebin Lam, Kwok-Yan Xian Univ Posts & Telecommun Sch Cyberspace Secur Xian Shaanxi Peoples R China Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian Shaanxi Peoples R China Xi An Jiao Tong Univ Sch Comp Sci & Technol Xian Shaanxi Peoples R China

Local Differential Privacy (LDP) can provide each user with strong privacy guarantees under untrusted data curators while ensuring accurate statistics derived from privatized data. Due to its powerfulness, LDP has been widely adopted to protect privacy in various tasks (e.g., heavy hitters discovery, probability estimation) and systems (e.g., Google Chrome, Apple iOS). In particular, (epsilon, delta)-LDP has been studied in related statistical tasks like private learning and hypothesis testing, but is mainly achieved by using Gaussian mechanism, leading to the limited data utility. In this paper, we investigate several novel mechanisms that achieve (epsilon, delta)-LDP with higher data utility in collecting and analyzing users' data. Specifically, we first design two (epsilon, delta)-LDP algorithms for mean estimations on multi-dimensional numeric data, which can ensure higher accuracy than the optimal Gaussian mechanism. Then, we investigate different local protocols for frequency estimations on categorical attributes under (epsilon, delta)-LDP. Based on the proposed mechanisms, we further study on (epsilon, delta)-LDP-compliant stochastic gradient descent algorithms for machine learning models. Besides, the theoretical analysis of the error bound and the variance of the proposed algorithms are also presented in the paper. We have conducted extensive experiments on both real-world and synthetic datasets and demonstrated the high data utility of our proposed algorithms in the perspectives of simple data statistics tasks and complex machine learning tasks. The experimental results have shown that our proposed algorithms can effectively improve the data utility in different tasks while alleviating the privacy concerns of each individual. (C) 2020 Elsevier B.V. All rights reserved.

关键词： data collection and analysis (epsilon, delta)-local differential privacy Stochastic gradient descent data utility

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Automatic Multi-Vendor IED Fault data collection and analysis Solution 71

Automatic Multi-Vendor IED Fault Data Collection and Analysi...

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71st Annual Conference on Protective Relay Engineers (CPRE)

作者： Salvador, Armand Rodriguez, Simon SUBNET Solut Inc Calgary AB Canada SUBNET Solut Inc Business Dev Calgary AB Canada

ISBN: (纸本)9781538661277

Smart automation technologies aim to improve efficiency and productivity in several areas. Specifically for power system disturbances, automation can greatly reduce capital and labor costs by not only reducing travel time to substations to collect event data but streamline event response processes. A key concept in fully achieving this type of automation involves solutions that not only support automated fault data collection from IEDs, but automated fault data analysis as well. The fault data collection was a challenging feat for a utility from the Dominican Republic where their power system consisted of a breadth of multi-vendor devices such as SEL, GE, ABB, Siemens, ERLPhase, EMAX, APP, and Qualitrol. This presentation details the integration of three multi-vendor solutions that provided the utility with a complete vendor agnostic system to achieve the following benefits: A centralized IED management solution that supports automatic multi-vendor event data retrieval Email notification, version control and archival of collected records Secure authentication to a web-based interface to access and conduct in-depth post-event analysis Automatic conversion of proprietary event record formats to open standards such as COMTRADE Automatic event record analysis that summarizes disturbances and calculates Takagi, Modified Takagi, and Novosel fault location Ability to integrate with other business intelligence systems such as Enterprise Resource Planning systems like SAP to historians from OSIsoft, Schneider Wonderware eDNA, and Automsoft that can be utilized for breaker analytics and trending During this integration, several fault analysis applications ranging for open source, vendor-specific, and third-party applications such as EPRI openXDA, SEL microwave, GE Enervista, Siemens SIGRA, and Wavewin were all integrated into the complete solution. This was done to support in-depth fault analysis for any fault data format when automatic conversion to an open standard was not

关键词： Substations Monitoring Maintenance engineering Circuit faults Real-time systems Relays Substations Circuit faults Maintenance engineering real-time systems relay event log Automation Dominican Republic data collection and analysis enterprise resource planning system AUTOMATIC faults Solutions

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A data collection and analysis framework to improve the performance of energy-intensive commercial buildings

A data collection and analysis framework to improve the perf...

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2014 International Conference on Computing in Civil and Building Engineering

作者： Azar, Elie Menassa, Carol C. Department of Civil and Environmental Engineering University of Wisconsin-Madison 2256 Engineering Hall 1415 Engineering Dr. MadisonWI United States John L. Tishman Faculty Scholar Department of Civil and Environmental Engineering University of Michigan 2350 Hayward St. Ann ArborMI United States

ISBN: (纸本)9780784413616

Commercial buildings show large discrepancies between estimated and actual energy consumption levels. Important challenges specifically lay in understanding the influence of human actions (by occupants and facility managers) on energy use and their contribution to commonly observed high energy consumption levels. This is particularly relevant in energy-intensive buildings, such as laboratory facilities, which can typically consume up to five times more energy than other types of commercial buildings. This paper presents a framework to (1) collect relevant data about building energy performance and occupancy, (2) mine data, and (3) adapt and use energy analysis methods to understand the influence of occupants on energy performance, detect inefficiencies in the operation of building systems, and propose solutions. The framework is illustrated though a case study on a laboratory building in Madison, WI, identifying an excess of 40 percent in the energy consumption of the Heating, Ventilation and Air Conditioning System (HVAC). © ASCE 2014.

关键词： energy consumption commercial buildings Energy performance heating ventilation and air conditioning data collection and analysis Building systems Frameworks data collection Methods Buildings

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data collection and analysis of GitHub repositories and users

Data collection and analysis of GitHub repositories and user...

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Fragkiskos Chatziasimidis Ioannis Stamelos Gnomon Informatics SA Thessaloniki Greece Department of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

In this paper, we present the collection and mining of GitHub data, aiming to understand GitHub user behavior and project success factors. We collected information about approximately 100K projects and 10K GitHub users//owners of these projects, via GitHub API. Subsequently, we statistically analyzed such data, discretized values of features via k-means algorithm, and finally we applied apriori algorithm via weka in order to find out association rules. Having assumed that project success could be measured by the cardinality of downloads we kept only the rules which had as right par a download cardinality higher than a threshold of 1000 downloads. The results provide intersting insight in the GitHub ecosystem and seven success rules for GitHub projects.

关键词： GitHub GitHub API association rules discretization k-means open source project success Association rules open source Discretization Downloading data collection and analysis base number Gallirallus australis Consumers K-means algorithm WAREHOUSE data collection Methods

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Exploration on data collection and analysis System Based on Integrated SIFT Algorithm

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Procedia Computer Science 2024年 243卷 388-395页

作者： Yijin Sun College of Basic Military and Political Education National University of Defense Technology Changsha Hunan China

With the development of applications related to image processing technology, the target requirements of data acquisition and analysis systems are constantly being optimized. Research on data acquisition and analysis based on the integrated SIFT (Scale Invariant Feature Transform) algorithm is becoming increasingly important. The construction of a data collection and analysis system focuses on ensuring efficient and accurate data collection and analysis to provide valuable insights and decision support. Key priorities include determining data requirements and objectives, designing appropriate data collection methods and tools, establishing reliable data storage and management systems, developing effective data analysis algorithms and models, and ensuring data security and privacy protection. This article analyzed the theoretical analysis of feature point extraction algorithm and the process steps and application of integrated SIFT algorithm. With the help of dimensionality reduction processing, the SIFT algorithm was improved and optimized. Combined with the scale space calculation formula, The conclusion is as follows: On the basis of image processing, the data collection and analysis system using the improved integrated SIFT algorithm on the five selected image file samples has improved the accuracy of feature point matching, with a comprehensive average improvement of 7.6%. The efficiency of feature point extraction has also been improved, with a comprehensive average improvement of about 8%. This indicated that the data collection and analysis system based on the improved integrated SIFT algorithm has good practical application results in feature point matching and extraction.

关键词： integrated SIFT algorithm data collection and analysis dimensionality reduction processing system design

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Breaking Down the Barriers: Challenges With Development and Implementation of an Industry-Sponsored Antimicrobial Stewardship data collection and analysis Tool

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CLINICAL INFECTIOUS DISEASES 2014年第SUPPL_3期59卷 S179-S184页

作者： Hermsen, Elizabeth D. McDaneld, Patrick M. Eiland, Edward H., III Destache, Christopher J. Lusardi, Katherine Estrada, Sandy J. Mercier, Renee-Claude DePestel, Daryl D. Lamp, Kenneth C. Anderson, Evette Chung, Thomas J. McKinnon, Peggy S. Cubist Pharmaceut Global Med Affairs Lexington MA 02421 USA Univ Nebraska Med Ctr Coll Pharm Dept Pharm Practice Omaha NE USA Massachusetts Coll Pharm & Hlth Sci Dept Pharm Practice Worcester MA USA Huntsville Dist Mem Hosp Dept Pharm Huntsville AL USA Creighton Univ Sch Pharm & Hlth Profess Omaha NE 68178 USA Univ Arkansas Med Sci Med Ctr Dept Pharm Little Rock AR 72205 USA Lee Mem Hlth Syst Dept Pharm Ft Myers FL USA Univ New Mexico Coll Pharm Albuquerque NM 87131 USA

Partnership between clinicians and the pharmaceutical industry with a focus on antimicrobial stewardship research initiatives is a necessary step toward meeting the shared goals of combating inappropriate antimicrobial use, improving patient outcomes, and minimizing resistance development. Achieving these goals requires outcomes-focused data collection and monitoring tools for antimicrobial stewardship programs (ASP) that consider real-world data about how antimicrobials are used to treat patients. Here we highlight the experiences and challenges associated with the development and implementation of an industry-sponsored electronic antimicrobial stewardship data collection and analysis tool (AS-DCAT). The benefits and risks of the industry-sponsored AS-DCAT from the perspectives of the sponsoring company and participating sites are discussed. Barriers encountered as well as general considerations and recommendations for preventing or overcoming those barriers for future studies and tool development are provided.

关键词： antimicrobial stewardship appropriate use data collection and analysis electronic data capture

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Autonomous Robotic System for Bridge Deck data collection and analysis

Autonomous Robotic System for Bridge Deck Data Collection an...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Hung Manh La Nenad Gucunski Seong-Hoon Kee Jingang Yi Turgay Senlet Luan Nguyen Department of Computer Science and Engineering University of Nevada Reno NV 89557 USA Department of Civil and Environmental Engineering Rutgers University Piscataway NJ 08854 USA Department of Architectural Engineering Dong-A University Busan Korea Department of Mechanical and Aerospace Engineering Rutgers University Piscataway NJ 08854 USA Department of Computer Science Rutgers University Piscataway NJ 08854 USA

ISBN: (纸本)9781479969357

Bridge deck inspection is conducted to identify bridge condition deterioration and, thus, to facilitate implementation of appropriate maintenance or rehabilitation procedures. In this paper, we report the development of a robotic system for bridge deck data collection and analysis. The robotic system accurately localizes itself and autonomously maneuvers on the bridge deck to collect visual images and conduct nondestructive evaluation (NDE) measurements. The developed robotic system can reduce the cost and time of the bridge deck data collection. Crack detection and mapping algorithm to build the deck crack maps is presented in detail. The electrical resistivity (ER), impact-echo (IE) and ultrasonic surface waves (USW) data collected by the robot are analyzed to generate the corrosion, delamination and concrete elastic modulus maps of the deck. The presented robotic system has been successfully deployed to inspect numerous bridges.

关键词： Bridge Decks data collection and analysis Elastic Modulus Robot

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Illuminating Issues in Bus Stop Lighting: A Case Study of Los Angeles

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TRANSPORTATION RESEARCH RECORD 2025年

作者： Reginald, Monisha Massachusetts Bay Transportat Author Operat Planning Scheduling & Strategy Boston MA 02116 USA

Providing adequate nighttime lighting at bus stops is integral to providing safe, comfortable, and gender-equitable transit services. Despite the volume of research establishing the importance of bus stop lighting, little research has been done to understand the distribution of adequate lighting at bus stops. This research uses Los Angeles, U.S., as a case study and draws on the results from over 200 nighttime environmental assessments conducted at bus stops in three neighborhoods to describe the adequacy of lighting at stops and the determinants of lighting levels. The results show that only about half of the assessed stops were adequately lit and only about a quarter were well-lit. Lighting deficiencies were particularly concentrated in certain geographic areas, and stops were the most likely to be poorly lit in the lowest-income neighborhood included in the study. The presence of a bus shelter with integrated lighting is the most significant determinant of bus stop lighting levels, but the lighting levels at the nearest streetlight and proximity to well-lit buildings also significantly affect bus stop lighting. This research then compares these findings with analysis of data on streetlight locations to investigate the limitations of using existing public data to assess nighttime lighting when other data are not available. The results show that analyses of streetlight locations can paint an incomplete or even misleading picture of trends in the distribution of adequate lighting within cities or transit systems, illustrating the importance of collecting data on actual lighting outcomes at bus stops.

关键词： public transportation bus stops data collection and analysis transporation equity transportation safety

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Applying process mining techniques in software process appraisals

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INFORMATION AND SOFTWARE TECHNOLOGY 2017年 87卷 19-31页

作者： Valle, Arthur M. Santos, Eduardo A. P. Loures, Eduardo R. Pontificia Univ Catolica Parana Imaculada Conceicao 1155 BR-80215901 Curitiba Parana Brazil Waikato Inst Technol Tristam StPrivate Bag 3036 Hamilton 3240 New Zealand Univ Fed Parana Pref Lothario Meissner 632 BR-80210170 Curitiba Parana Brazil

Context: Process assessments are performed to identify the current maturity of organizations in relation to best practices. Existing process assessment methods, although widely used, have limitations such as: dependence on the competencies of appraisers;high amount of effort and resources required;subjectivity to analyze data and to judge on the implementation of practices;low confidence in sampling and its representativeness. Currently, due to the increasing use of information systems to support process execution, detailed information on the implementation of processes are recorded as event logs, transaction logs, etc. This fact enables the usage of process mining techniques as a powerful tool for process analysis. It allows using a significant amount of data with agility and reliability for process assessments. Objective: The objective of this paper is to present the development and application of a feasible, usable and useful method, which reduces the limitations of current SCAMPI method and defines how to apply process mining techniques in SCAMPI-based process appraisals. Method: Research method comprises nine steps that were performed in a manner that raised questions in the first four steps were answered by the last four steps of the research design. Results: The method "Process Mining Extension to SCAMPI" was designed, developed, applied in two cases and submitted for review by experts who judged it viable, usable, and useful. Conclusions: As per this research, process mining techniques are suitable to be applied in software process assessments since they are aligned with the purposes of data collection and analysis tasks. In addition to that, the resulting method was judged by experts as something that reduces identified limitations of one of the most used process assessment method. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Process mining Software process assessment SCAMPI data collection and analysis Process Mining Extension to SCAMPI

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