Technology Refresh Analysis Sample Clauses

Technology Refresh Analysis. The Contractor shall provide an analysis in the form of a plan for technology refresh of the proposed system. This shall be based on Product Supportability Analysis and requirements to mitigate obsolescence/supportability issues but using a twenty year timeframe. Analysis shall include: • Predicted schedule for required refresh(s), identified as a unique Refresh configuration (TR 1, TR 2…). This schedule shall be overlaid on proposed production schedule of baseline configuration. • Discussion of the level of hardware and software changes required for each technical refresh. • Required milestones to meet proposed technical refresh i.e. life of type buys, bridge buys, recover/refurbish assets removed as part of technical refresh installs to support remaining baselines etc. • ILS considerations such as Training or Technical documentation that may be a significant cost driver as a result of Technical refresh. CDRL: A038
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Related to Technology Refresh Analysis

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  • Data Analysis In the meeting, the analysis that has led the College President to conclude that a reduction- in-force in the FSA at that College may be necessary will be shared. The analysis will include but is not limited to the following: ● Relationship of the FSA to the mission, vision, values, and strategic plan of the College and district ● External requirement for the services provided by the FSA such as accreditation or intergovernmental agreements ● Annual instructional load (as applicable) ● Percentage of annual instructional load taught by Residential Faculty (as applicable) ● Fall Full-Time Student Equivalent (FFTE) inclusive of dual enrollment ● Number of Residential Faculty teaching/working in the FSA ● Number of Residential Faculty whose primary FSA is the FSA being analyzed ● Revenue trends over five years for the FSA including but not limited to tuition and fees ● Expenditure trends over five years for the FSA including but not limited to personnel and capital ● Account balances for any fees accounts within the FSA ● Cost/benefit analysis of reducing all non-Residential Faculty plus one Residential Faculty within the FSA ● An explanation of the problem that reducing the number of faculty in the FSA would solve ● The list of potential Residential Faculty that are at risk of layoff as determined by the Vice Chancellor of Human Resources ● Other relevant information, as requested

  • SERVICE MONITORING, ANALYSES AND ORACLE SOFTWARE 11.1 We continuously monitor the Services to facilitate Oracle’s operation of the Services; to help resolve Your service requests; to detect and address threats to the functionality, security, integrity, and availability of the Services as well as any content, data, or applications in the Services; and to detect and address illegal acts or violations of the Acceptable Use Policy. Oracle monitoring tools do not collect or store any of Your Content residing in the Services, except as needed for such purposes. Oracle does not monitor, and does not address issues with, non-Oracle software provided by You or any of Your Users that is stored in, or run on or through, the Services. Information collected by Oracle monitoring tools (excluding Your Content) may also be used to assist in managing Oracle’s product and service portfolio, to help Oracle address deficiencies in its product and service offerings, and for license management purposes.

  • Research Use Reporting To assure adherence to NIH GDS Policy, the PI agrees to provide annual Progress Updates as part of the annual Project Renewal or Project Close-out processes, prior to the expiration of the one (1) year data access period. The PI who is seeking Renewal or Close-out of a project agree to complete the appropriate online forms and provide specific information such as how the data have been used, including publications or presentations that resulted from the use of the requested dataset(s), a summary of any plans for future research use (if the PI is seeking renewal), any violations of the terms of access described within this Agreement and the implemented remediation, and information on any downstream intellectual property generated from the data. The PI also may include general comments regarding suggestions for improving the data access process in general. Information provided in the progress updates helps NIH evaluate program activities and may be considered by the NIH GDS governance committees as part of NIH’s effort to provide ongoing stewardship of data sharing activities subject to the NIH GDS Policy.

  • For Product Development Projects and Project Demonstrations  Published documents, including date, title, and periodical name.  Estimated or actual energy and cost savings, and estimated statewide energy savings once market potential has been realized. Identify all assumptions used in the estimates.  Greenhouse gas and criteria emissions reductions.  Other non-energy benefits such as reliability, public safety, lower operational cost, environmental improvement, indoor environmental quality, and societal benefits.  Data on potential job creation, market potential, economic development, and increased state revenue as a result of the project.  A discussion of project product downloads from websites, and publications in technical journals.  A comparison of project expectations and performance. Discuss whether the goals and objectives of the Agreement have been met and what improvements are needed, if any.

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  • Laboratory Services Covered Services include prescribed diagnostic clinical and anatomic pathological laboratory services and materials when authorized by a Member's PCP and HPN’s Managed Care Program.

  • Industrial Operations Analyst (IOA ‌ The IOA is a GSA Government official who audits Contractor records and conducts Contractor Assistance Visits (CAVs) to the Contractor’s place of business to assist the Contractor with task order reporting, Contract Access Fee (CAF) management, and other general contract administration functions deemed necessary by the Government.

  • Statistical Analysis 31 F-tests and t-tests will be used to analyze OV and Quality Acceptance data. The F-test is a 32 comparison of variances to determine if the OV and Quality Acceptance population variances 33 are equal. The t-test is a comparison of means to determine if the OV and Quality Acceptance 34 population means are equal. In addition to these two types of analyses, independent verification 35 and observation verification will also be used to validate the Quality Acceptance test results.

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