Table 7a Sample Clauses

Table 7a. Statistical targets and milestones relating to your applicants, entrants or student body Reference number Please select target type from the drop-down menu Description (500 characters maximum) Is this a collaborative target? Baseline year Baseline data Yearly milestones (numeric where possible, however you may use text) Commentary on your milestones/targets or textual description where numerical description is not appropriate (500 characters maximum) T16a_01 HESA T1b - Low participation neighbourhoods (POLAR3) (Young, full-time, undergraduate entrants) To achieve a participation rate of Young Full time Undergraduates (HESA Table T1b) of 17.5% from Lower Participation Neighbourhoods (POLAR 3), by 2020. No 2013-14 16.4% 16.7% 16.9% 17.1% 17.3% 17.5% T16a_02 HESA T3b - No longer in HE after 1 year & in low participation neighbourhoods (POLAR 3) (Young, full-time, first degree entrants) To reduce the non-continuation for young FT UGs from LPNs to 7.5% by 2020 (as measured by HESA Table T3b – POLAR 3 data) No 2012-13 8.7% 8.3% 8.1% 7.9% 7.7% 7.5% T16a_03 Other statistic - Progression to employment or further study (please give details in the next column) To increase the percentage of full-time, UK, first degree graduates from LPN (POLAR 3 quintiles 1 or 2) entering professional/managerial employment or further study to 68% by 2020. No 2013-14 56% 60% 62% 64% 66% 68% Based on institutional analysis of DLHE data (the year relates to the year of the survey, the year after graduation) T16a_04 Other statistic - Other (please give details in the next column) To increase positive response in the National Student Survey to the statement ‘As a result of my course I believe my career prospects have improved’ to 78% in 2020 (from 68% in 2013) No 2013-14 68% 70% 72% 74% 76% 78% T16a_05 Other statistic - Care-leavers (please give details in the next column) To increase the number of Care Leavers at MMU to 75 by 2020, from 57 in 2013/14 (based on number of students receiving the MMU Care Leaver Bursary) No 2013-14 57 60 63 66 70 75 T16a_06 Other statistic - Low-income backgrounds (please give details in the next column) Increase the numbers of students from low income backgrounds (household income of £25,000 or less) taking a sandwich year No 2013-14 155 Monitor and publish figure Monitor and publish figure Monitor and publish figure Monitor and publish figure Monitor and publish figure Notes Alongside applicant and entrant targets, we encourage you to provide targets around...
Sample 1
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Table 7a. Statistical targets and milestones relating to your applicants, entrants or student body Reference number Please select target type from the drop-down menu Description (500 characters maximum) Is this a collaborative target? Baseline year Baseline data Yearly milestones (numeric where possible, however you may use text) Commentary on your milestones/targets or textual description where numerical description is not appropriate (500 characters maximum) T16a_04 Other statistic - Progression to employment or further study (please give details in the next column) Maintain completion levels at current rates No 2013-14 89% 89% 90% 91% 92% 92% T16a_05 Other statistic - Other (please give details in the next column) Maintain mature student % No 2012-13 60% 61% 62% 62% 62% 62% T16a_06 Other statistic - Other (please give details in the next column) Increase % of part time HE students No 2012-13 37% 40% 41% 42% 43% 43% T16a_07 Other statistic - Other (please give details in the next column) Increase progression from FE to HE No 2014-15 30% 35% 40% 41% 41% 41% T16a_08 Other statistic - Low-income backgrounds (please give details in the next column) LCoM only – increase % of Saturday Music School students from low-income backgrounds No 2014-15 0.2 0.21 0.22 0.23 0.24 0.25 Notes Alongside applicant and entrant targets, we encourage you to provide targets around outreach and student success work (including collaborative work where appropriate) or other initiatives to illustrate your progress towards increasing access, student success and progression. These should be measurable outcomes ‐based targets and should focus on the number of beneficiaries reached by a particular activity/programme or the number of schools worked with, and what the outcomes were, rather than simply recording the nature/number of activities.
Sample 1
Table 7a. Likelihood of Beginning to Pay, Separate Analyses by Earnings Low-Income (earned < $20,000 in year prior to order) Not Low-Income (earned >= $20,000 in year prior to order) Coefficient‌ Standard Error Hazard Ratio Coefficient Standard Error Hazard Ratio Total General letter This month 0.73***‌ 0.04‌ 2.08‌ 0.35***‌ 0.06‌ 1.41‌ †‌ Last month 0.33*** 0.04 1.39 -0.02 0.07 0.98 † 2 months ago 0.24*** 0.05 1.27 -0.03 0.09 0.97 † 3 or more months ago 0.21*** 0.04 1.23 -0.08 0.08 0.93 † Notice of intent to suspend This month 0.68***‌ 0.08‌ 1.97‌ 0.63***‌ 0.14‌ 1.88‌ Last month 0.16 0.12 1.17 0.10 0.23 1.11 2 months ago 0.01 0.14 1.01 0.17 0.28 1.19 3 or more months ago 0.07 0.09 1.07 0.09 0.22 1.09 License suspension This month 0.31*‌ 0.16‌ 1.36‌ 0.45‌ 0.30‌ 1.57‌ Last month 0.08 0.19 1.09 0.52 0.45 1.69 2 months ago -0.22 0.24 0.81 -0.32 0.74 0.72 3 or more months ago -0.02 0.11 0.98 0.13 0.40 1.14 Court hearing This month 1.01***‌ 0.05‌ 2.75‌ 0.96***‌ 0.10‌ 2.62‌ Last month 0.40*** 0.08 1.49 0.38* 0.17 1.46 2 months ago 0.48*** 0.09 1.61 0.27 0.22 1.31 3 or more months ago 0.38*** 0.05 1.47 0.12 0.17 1.13 † Contempt This month 0.66***‌ 0.07‌ 1.93‌ 0.75***‌ 0.14‌ 2.12‌ Last month 0.37** 0.12 1.45 0.33 0.30 1.40 2 months ago 0.17 0.15 1.19 0.52 0.37 1.68 3 or more months ago 0.21** 0.07 1.23 0.86** 0.27 2.36 †‌ n 8,680 2,774 11,454 Log likelihood (-2) 121,225 35,218 167,141 * p<.05, ** p<.01, *** p<.001‌ † subgroups significantly differ from each other at p<.05 Note: N=329 missing information on earnings are excluded from this subgroup analysis. Xxx proportional hazard model, with Efron treatment of ties. Model also includes demographic controls. different actions have different lags). Suspending licenses does not have a significantly different relationship between the two subgroups, though it is only significantly associated with beginning to pay for low-income fathers, for whom the standard error is smaller. While letters are associated with beginning to pay for both groups of fathers, the relationship is significantly stronger for low-income fathers. Table 7b examines separate relationships for those who were initial nonpayers compared to those who paid initially but then fell into nonpayment. All enforcement tools are significantly associated with beginning to pay for both groups except for license suspensions (which is significant for initial payers only, though relatively large standard errors and the small incidence means there is no significant difference ...
Sample 1
Table 7a. Statistical targets and milestones relating to your applicants, entrants or student body Reference number Please select target type from the drop-down menu Description (500 characters maximum) Is this a collaborative target? Baseline year Baseline data Yearly milestones (numeric where possible, however you may use text) Commentary on your milestones/targets or textual description where numerical description is not appropriate (500 characters maximum)
Sample 1
Table 7a. Statistical targets and milestones relating to your applicants, entrants or student body Number Please select target type from the drop-down menu Description (500 characters maximum) Is this a collaborative target? Baseline year Baseline data Yearly milestones (numeric where possible, however you may use text) Commentary on your milestones/targets or textual description where numerical description is not appropriate (500 characters maximum) 2014-15 2015-16 2016-17 2017-18 2018-19 1 HESA T1b - State School (Young, full-time, undergraduate entrants) Restore 2009/10 levels of participation for young full-time undergraduates from state schools to 95.4% by 2016/17 No 2009/10 95.4% 94.5% 95% 95.4% In the 2012/13 agreement MMU anticipated that participation would drop nationally in the first two years following the introduction of tuition fees and made a commitment to arresting that fall and restoring participation levels of target groups to current levels over the next five years. Early indications suggest this may be a very ambitious target and once the actual figures are available we will review this position and may alter our targets accordingly. 2 HESA T1b - Low participation neighbourhoods (POLAR2) (Young, full-time, undergraduate entrants) Restore 2009/10 levels of participation for young full-time undergraduates from Low Participation Neighbourhoods to 15.5% by 2016/17 No 2009/10 15.5% 14.5% 15% 15.5% In the 2012/13 agreement MMU anticipated that participation would drop nationally in the first two years following the introduction of tuition fees and made a commitment to arresting that fall and restoring participation levels of target groups to current levels over the next five years. Early indications suggest this may be a very ambitious target and once the actual figures are available we will review this position and may alter our targets accordingly. 3 HESA T3b - No longer in HE after 1 year & in low participation neighbourhoods (POLAR 2) (Young, full-time, first degree entrants) To half the difference between the non- continuation rate for young full-time first degree entrants from LPNs and that for those from other neighbourhoods No 2009/10 3.5% 2.5% 2% 1.75% Non-continuation rate for those from LPNs in 2009/10 was 12.8% compared with 9.3% for other neibourhoods, resulting in the current 3.5% difference . 4 HESA T3b - No longer in HE after 1 year & in low participation neighbourhoods (POLAR 2) (Young, full-time, first degree entrants) To improve the ...
Sample 1
Table 7a. Exposure results for pesticide A in mg per dosimeter for mixer/loaders & operators (TRIAL SET 1) Amount per quantity handled (mg) PESTICIDE A ML-1 ML-2 ML-3 ML-4 ML-5 ML-6 OP-1 OP-2 OP-3 OP-4 OP-5 OP-6 outer jacket 0.049 1.502 0.066 0.011 0.018 0.007 2.691 2.577 4.948 0.746 0.372 0.797 outer trousers 0.028 0.037 0.010 0.007 <LOQ 0.004 5.460 4.941 5.222 0.373 0.373 0.754 inner shirt <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ 0.005 0.020 0.010 0.009 <LOQ 0.029 inner pants <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ 0.026 0.033 0.014 0.005 0.007 0.012 cap <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ 0.002 0.015 0.008 0.001 0.001 0.002 inner gloves <LOQ 0.297 0.030 0.006 0.001 0.005 0.001 0.001 0.002 0.008 <LOQ 0.004 protective gloves 0.398 0.359 0.218 0.005 <LOQ 0.001 0.464 0.413 0.340 0.091 0.037 0.058 ML1, ML2, ML3 and OP1, OP2, OP3 handled pesticide A (morning) while ML4, ML5, ML6 and OP4, OP5, OP6 handled pesticide B (afternoon) Table 7b: Exposure results for pesticide B in mg per dosimeter for mixer/loaders and operators (TRIAL SET 1) Amount per quantity handled (mg) PESTICIDE B ML-4 ML-5 ML-6 OP-4 OP-5 OP-6 outer jacket 0.113 0.101 0.028 0.855 0.633 1.134 outer trousers <LOQ 0.086 0.005 0.226 0.631 1.114 inner shirt <LOQ <LOQ 0.005 0.003 0.004 0.005 inner pants 0.003 0.003 0.010 0.004 0.006 0.007 cap <LOQ <LOQ <LOQ 0.002 0.016 0.005 inner gloves 0.009 0.239 0.101 0.001 0.001 0.009 protective gloves 1.510 1.299 1.782 0.093 0.122 0.141 ML4, ML5, ML6 and OP4, OP5, OP6 handled pesticide B (afternoon) Table 7c: Exposure results for pesticide A in mg a.s./ kg a.s. handled for mixer/loaders and operators (TRIAL SET 1) Amount per quantity handled (mga.s./Kg a.s.) PESTICIDE A ML-1 ML-2 ML-3 ML-4 ML-5 ML-6 OP-1 OP-2 OP-3 OP-4 OP-5 OP-6 outer jacket 0.602 18.482 0.817 0.136 0.227 0.086 39.4 34.3 60.9 10.9 4.95 9.81 outer trousers 0.344 0.461 0.126 0.81 <LOQ 0.050 80.0 65.7 64.3 5.47 4.96 9.28 inner shirt <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ 0.075 0.268 0.125 0.131 <LOQ 0.362 inner pants <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ 0.384 0.434 0.177 0.071 0.097 0.152 cap <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ 0.026 0.204 0.104 0.009 0.020 0.021 inner gloves <LOQ 3.653 0.373 0.077 0.007 0.061 0.007 0.019 0.022 0.115 <LOQ 0.044 protective gloves 4.899 4.415 2.680 0.058 <LOQ 0.016 6.800 5.497 4.188 1.331 0.490 0.710 ML1, ML2, ML3 and OP1, OP2, OP3 handled pesticide A (morning) while ML4, ML5, ML6 and OP4, OP5, OP6 handled pesticide B (afternoon) Table 7d: Exposure results for pesticide B in mg a.s./ kg a.s. handled for mixer/loaders & oper...
Sample 1

Related to Table 7a

  • Table 2 Software Subscription Use Case OpenShift Enterprise OpenShift Enterprise Broker Infrastructure OpenShift Enterprise is intended to be used as a platform as a service and will be supported only when used in that capacity. OpenShift Enterprise is not supported on non-server hardware such as desktops or workstations. OpenShift Enterprise is intended for use on a dedicated Physical Node or Virtual Guest; running other applications and/or programs of any type on the Physical Node or Virtual Guest can have a negative impact on the function and/or performance. Red Hat JBoss Enterprise Application Platform for OpenShift and/or Red Hat JBoss EAP for xPaaS will be supported in accordance with the terms of Exhibit 1.B.

  • Table 3 Appendix Information

  • Table 1b Allocation of Commonwealth supported places for designated courses of study for 20191 Cluster No. Funding cluster Number of designated undergraduate places (excluding medical places) for 2019 grant year (EFTSL)2 Number of undergraduate medical places for 2019 grant year (EFTSL) Number of non- research postgraduate places (excluding medical places) for 2019 grant year (EFTSL) Number of postgraduate medical places for 2019 grant year (EFTSL)3 Total number of Commonwealth supported places for 2019 grant year (EFTSL) 1 Law, accounting, administration, economics, commerce 340 0 25 0 365 5 Clinical psychology, allied health, foreign languages, visual and performing arts 19 0 95 0 114 6 Nursing 0 0 215 0 215 8 Medicine, dentistry, veterinary science, agriculture 0 0 5 444 449 Total 360 0 875 444 1679 NOTES:

  • Table 2 (definition of “Casino Gross Revenue”) 15(e) 2 (definition of “Commissioning”) 19 2 (definition of “Committee’s Nominated Representative) 20(1) 6(1)(c) 20(2) 7(8)(a) 21(d) 11(1) 21(e) 11(2) 22(2) 11(3) 23(b) 14(d) 33(2) 15(a)(B) 35(1) 15(b)(i) 35(2) 15(c) 36(b) 15(d) 36(c)

  • Table 4 Ending this Addendum when the Approved Addendum Changes Which Parties may end this Addendum as set out in Section 19: Importer Exporter Ending this Addendum when the Approved Addendum changes Part 2: Mandatory Clauses Entering into this Addendum

  • Table A Billable RU Server Categories Category Primary Capability Description Example Resource Unit(s) through CY5 Resource Unit(s) effective with Hybrid Cloud through the Term. Application Servers hosting agency business applications Database, Middleware, Webhosting/Web Proxy, Security Apps, Reporting Services and Performance Monitoring Apps, Collaborative (e.g. SharePoint) STM, HSC STM, HSC Physical Appliance Means a specialized computing device with pre-integrated and pre-configured hardware and/or software packaged to provide a “turn-key” solution. Google Appliance Consolidated Infrastructure Virtual Appliance Means a specialized computing service with pre-integrated software running on DCS Multi-Customer Servers, software and storage. Google Appliance, HSC Consolidated Infrastructure, HSC Email Servers providing Email Services Exchange, Groupwise, Remote email access proxy, Mail stores Email Account, no HSC STM, HSC Email - ADFS Servers providing single sign-on (federated) access to Microsoft Office 365 Email Services ADFS For DCS Customers with O365 Services acquired through the Microsoft Xxxxxx 000 XXX: Xx XX, xx XXX; $4,250 charge per server, incurred at stand up and refresh For DCS Customers with O365 Services not acquired through the Microsoft Office 365 OEA: STM, HSC For DCS Customers with O365 Services not acquired through the Microsoft Office 365 OEA bringing existing ADFS servers into STM at refresh or with new procurement, HSC For DCS Customers with O365 for Education: For existing servers, no RU, no HSC, 5 project pool hours/mo. per server until refresh; STM at refresh or with new procurement, HSC scope: STM, Server Installation Fee or HSC** For DCS Customers with O365 for Education: No RU, no HSC; $4,250 charge per server, incurred at stand up and refresh; 5 project pool hours/mo. per server Enterprise SMTP Relay Servers providing SMTP relay services to internal Mail servers and Application Servers SMTP Mail Relay host Email Account, no HSC STM, HSC File and Print Servers hosting End User corporate file shares or print queue solutions not inclusive of the Enterprise File and Print solution. File Shares, Print Queues STM, HSC STM, HSC Enterprise File and Print Servers hosting End User corporate file shares or print queue solutions as part of the Enterprise File/Print Services RU. File Shares, Print Queues Enterprise File/Print Services RU, no HSC Enterprise File/Print Services RU, no HSC Non- Consolidated SCCM Support Servers hosting PC images used for desktop support. System Center Configuration Manager Non- Consolidated SCCM Support RU, HSC STM, HSC Remote File Services Servers providing the ability to store, share and backup files using an online file server that can be synchronized to local storage. Ctera appliance Remote File Services RU, no HSC Remote File Services RU, no HSC Enterprise Gateway Servers providing End User remote access, and external file sharing. FTP, RAS, BES, Fax STM, HSC STM, HSC Presentation/ Terminal Servers provide for the processing of applications which have the presentation layer presented to connected thin PCs Citrix, Terminal Server STM, HSC STM, HSC Identity Management Solutions Systems independent from the Infrastructure Domain Services used to perform Identity Management functions such as define User access or to deliver services customized based on an “identity” or profile Oracle Identity Management, Quest Identity and Access Management, IBM Tivoli Identity and Access Manager STM, HSC STM, HSC Software Distribution Servers providing software distribution, remote management, asset inventory, and image development. Marimba, SMS, Ghost, LanDesk, Altiris, Image Servers Agency push to desktop – STM, HSC Agency push to desktop – STM, HSC SP – Infrastructure – No RU, Provider overhead SP – Infrastructure – No RU, Provider overhead Domain Services** Servers providing End User enterprise authentication and IP/Name resolution. DNS, DHCP, Radius, WINS, Domain Controllers, Active Directory, ISA Active Director Forests and Active Directory Infrastructure – No RU, Provider overhead STM, HSC *During a migration from Consolidated email accounts or Non-Consolidated email accounts to Microsoft Office 365 email accounts, the Charges for Email Servers shall change as described in Section 19.5(c) **Service Provider will evaluate a DCS Customer’s existing ADFS Servers at the time they are brought into scope. If Service Provider determines new ADFS servers are required, then the HSC shall apply. If new Servers are not required, then the Server Installation Fee shall apply. Infrastructure Servers and related disk and tape storage listed in Table B are not a billable Resource Unit and the cost to the Service Provider should be recovered through the other Server Resource Units. The following Table B provides the server categories and examples of servers considered Infrastructure Servers and are Non-Billable. Table B: Infrastructure Server Categories Category Primary Capability Description Example Resource Unit(s) Consolidated Data Centers – Infrastructure Network Servers and appliances that provide DCS network services VPN, LoadBalancer – No RU, Provider overhead DCS Customer- requested standalone devices – STM, HSC Non-DCS Network and Non-Consolidated – out of scope Enterprise Security Servers providing End User enterprise security management (authentication, protection, logging). Consolidated Data Center and Xxxxxxx Data Center Firewall, Server Anti-Virus, Intrusion Detection Infrastructure – No RU, Provider overhead Enterprise Backup Servers providing Third Party Vendor backup solutions. TSM, Legato, Backup Exec, Veritas Infrastructure – No RU, Provider overhead Enterprise Monitoring Servers providing Third Party Vendor monitoring, device fault management or capacity planning services for scope of services. BMC, EMC, Cisco Works, HP OpenView Infrastructure – No RU, Provider overhead Enterprise Scheduling Servers providing Third Party Vendor job scheduling solutions. Maestro, Tivoli Infrastructure – No RU, Provider overhead Software Distribution Servers providing software distribution, remote management, asset inventory, and image development. Marimba, SMS, Ghost, LanDesk, Altiris, Image Servers Agency push to desktop – STM, HSC SP – Infrastructure – No RU, Provider overhead

  • Table 1 4 If ‘Yes’ to any then you are likely required to carry out a DPIA under Article 35 GDPR. If ‘No’, to all then a DPIA may not be required. 1 xxxxx://xxx-xxx.xxxxxx.xx/legal-content/EN/TXT/?uri=CELEX:02016R0679-20160504

  • Table 7b - Other milestones and targets Reference Number Select stage of the lifecycle Please select target type from the drop-down menu Description (500 characters maximum) Is this a collaborative target? Baseline year Baseline data Yearly milestones (numeric where possible, however you may use text) Commentary on your milestones/targets or textual description where numerical description is not appropriate (500 characters maximum)

  • Measuring EPP parameters Every 5 minutes, EPP probes will select one “IP address” of the EPP servers of the TLD being monitored and make an “EPP test”; every time they should alternate between the 3 different types of commands and between the commands inside each category. If an “EPP test” result is undefined/unanswered, the EPP service will be considered as unavailable from that probe until it is time to make a new test.

  • Thresholds The threshold of a sample to constitute a positive result alcohol, drugs, or their metabolites is contained in the standards of one of the programs listed in MN Statute §181.953, subd 1. The employer shall, not less than annually, provide the unions with a list or access to a list of substances tested for under this LOA and the threshold limits for each substance. In addition, the employer shall notify the unions of any changes to the substances being tested for and of any changes to the thresholds at least thirty (30) days prior to implementation.

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