In many countries, coding education for lower grades typically begins with block coding and then progresses to learning text-based coding. Block coding is excellent for learning computational thinking without the burd...
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Thermal imaging cameras are predominantly employed for temperature detection in a wide range of production and life scenes. However, the efficacy of their temperature sensing efficiency is frequently influenced by int...
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Thermal imaging cameras are predominantly employed for temperature detection in a wide range of production and life scenes. However, the efficacy of their temperature sensing efficiency is frequently influenced by interface display mode and device display accuracy, subsequently impacting the efficiency of equipment temperature measurement and identification efficiency. In this study, a comprehensive analysis of color modes and screen resolution in infrared thermal imagers was conducted to ascertain the optimal color mode for different resolutions. To thoroughly investigate the key factors influencing the perception of the display interface in thermal imaging cameras, two sets of experiments were conducted, with a specific focus on factors associated with object contour perception and text recognition. The research findings underscore that color patterns effect object perceptual recognition, and rainbow or iron red color palette modes exhibit enhanced efficiency at lower resolutions (120ppi, 256ppi), whereas the grey palette mode demonstrates superior performance at higher resolutions. Additionally, it was observed that positive polarity augments text recognition, but the position of the character is independent of efficiency. This article provides invaluable guidance and recommendations for color and text coding design of infrared interface display with different display precision.
Purpose - Water is a critical and contentious resource in California, hence any changes in reservoir management requires coordination among many basin stakeholders. The Forecast-Informed Reservoir Operations (FIRO) pi...
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Purpose - Water is a critical and contentious resource in California, hence any changes in reservoir management requires coordination among many basin stakeholders. The Forecast-Informed Reservoir Operations (FIRO) pilot project at Lake Mendocino, California explored the viability of using weather forecasts to alter the operations of a United States Army Corps of Engineers (USACE) reservoir. The pilot project demonstrated FIRO's ability to improve water supply reliability, but also revealed the key role of a collaborative Steering Committee. Because Lake Mendocino's Viability Assessment did not explore the features of the Steering Committee, this study aims to examine the relationships and interactions between Steering Committee members that supported FIRO's implementation at Lake Mendocino. Design/methodology/approach - The project identified 17 key project participants who spoke at a FIRO workshop or emerged through chain-referrals. Using semi-structured interviews with these participants, the project examined the dynamics of human interactions that enabled the successful multi-institutional and multicriteria innovation as analyzed through text-coding. Findings - The results reveal the importance for FIRO Steering Committee members to understand the limitations and constraints of stakeholder counterparts at other organizations, the importance of building and safeguarding relationships, and the role of trust and belonging between members. The lessons learned suggest several interventions to support successful group collaboration dynamics for future FIRO projects. Originality/value - This study identifies features of the Steering Committee that contributed to FIRO's success by supporting collaborative negotiations of infrastructure operations within a multi-institutional and multi-criteria context.
Many scholars have called for qualitative research to demonstrate transparency and trustworthiness in the data analysis process. Yet these processes, particularly within inductive research, often remain shrouded in my...
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Many scholars have called for qualitative research to demonstrate transparency and trustworthiness in the data analysis process. Yet these processes, particularly within inductive research, often remain shrouded in mystery. We suggest that computer-aided/assisted qualitative data analysis software (CAQDAS) can support qualitative researchers in their efforts to present their analysis and findings in a transparent way, thus enhancing trustworthiness. To this end, we propose, describe, and illustrate working examples of six CAQDAS building blocks, three combined CAQDAS techniques, and two coder consistency checks. We argue that these techniques give researchers the language to write about their methods and findings in a transparent manner and that their appropriate use enhances a research project's trustworthiness. Specific CAQDAS techniques are rarely discussed across an array of inductive research processes. Thus, we see this article as the beginning of a conversation about the utility of CAQDAS to support inductive qualitative research.
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