TL;DR: This paper analyzes network and schedule choice using an "idealized" model that permits derivation of analytic, closed form expressions for airline and passenger costs and demonstrates that schedule reliability is highest for direct routing.
Abstract: The goal of this paper is to understand choices of networks and schedules by a profit maximizing airline. By "network" we mean the routing pattern for planes and by "schedule" we mean the frequency of service between cities and the amount of time put into the schedule to assure on-time arrival. This paper analyzes network and schedule choice using an "idealized" model that permits derivation of analytic, closed form expressions for airline and passenger costs. Many important conclusions are obtained. It is optimal for a profit maximizing airline to design its network and schedule to minimize the sum of airline and passenger costs. Profit maximizing choice of schedule frequency depends on the network. Direct service has lower schedule frequency than other networks. Parametric studies are performed on the effect of distance between cities, demand rate, and the number of cities served on the choice of the network. Some conclusions are: (1) If the distance between cities is very small, then direct service is optimal; otherwise, other networks, such as hub and spoke are optimal. (2) Similarly, for very high demand rates, direct service is optimal; and for intermediate values, hub and spoke is optimal. (3) If the number of cities is small, direct service dominates; and if it is large, hub and spoke is optimal. We note that any airline's schedule includes safety time as a buffer against delays, and we demonstrate that schedule reliability is highest for direct routing. Surprisingly, the amount of time that is added to the schedule to buffer delays is relatively less in direct networks than in other networks. This can explain the superior on-time performance and high equipment utilization of direct carriers such as Southwest Airlines.
TL;DR: In this paper, the authors evaluated the utility of four progress monitoring schedules that differed in frequency (once or twice weekly) and density (1 or 3 probes) and found that progress monitoring schedule frequency and density influenced the magnitude of SEb, density had a significant but negligible impact on SEE, and grade level had significant effect on slope and intercept.
Abstract: School-based professionals often use curriculum-based measurement of reading (CBM-R) to monitor the progress of students with reading difficulties. Much of the extant CBM-R progress monitoring research has focused on its use for making group-level decisions, and less is known about using CBM-R to make decisions at the individual level. To inform the administration and use of CBM-R progress monitoring data, the current study evaluated the utility of 4 progress monitoring schedules that differed in frequency (once or twice weekly) and density (1 or 3 probes). Participants included 79 students (43% female; 51% White, 25% Hispanic or Latino, 11% Black or African American, 1% other, 12% unknown) in Grades 2 (n = 45) and 4 (n = 34) who were monitored across 10 weeks (February to May). Consistent with a focus on individual-level decision making, we used regression and mixed-factorial analysis of variances (ANOVAs) to evaluate the effect of progress monitoring schedule frequency, schedule density, grade level, and their interaction effects on CBM-R intercept, slope, SE of the slope (SEb), and SE of the estimate (SEE). Results revealed that (a) progress monitoring schedule frequency and density influenced the magnitude of SEb, (b) density had a significant but negligible impact on SEE, and (c) grade level had a significant effect on slope and intercept. None of the interaction effects were statistically significant. Findings from this study have implications for practitioners and researchers aiming to monitor students' progress with CBM-R. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
TL;DR: In this paper, the authors developed an analytic model to study the effect of network design on an airline's cost and passengers' service level and found that the schedule frequency that minimizes total airline and passenger costs is a function of the network, and that direct service has lower schedule frequency than the other networks.
Abstract: This paper develops an analytic model to study the effect of network design on an airline's cost and passengers' service level. Four different types of networks are considered: direct, hub and spoke, tour and subtour. Service levels are measured by the cost borne by passengers due to travel time, schedule delay (the time difference between the ideal departure time and the actual departure time) and late arrival. Airline cost is the carrier's cost of operating its network. Results of the paper include that the schedule frequency that minimizes total airline and passenger costs is a function of the network, and that direct service has lower schedule frequency than the other networks. If passengers are sensitive to schedule delay, than a tour can be optimal, but if not, direct service can be optimal. Parametric studies are performed on the effect of distance between cities, demand rate and the number of cities served on the optimal network. If the distance between cities is small, direct service is optimal; if it is large, a tour is optimal; and for intermediate values, hub and spoke is optimal. If the number of cities is small, direct service dominates; if it is large, hub and spoke is optimal; and for intermediate values other networks are best. An airline's schedule includes time as a buffer against delays. This planned delay time increases passengers' travel time and airline cost since more aircraft are required, but reduces passengers' chances of arrival after the schedule time. It is shown that if schedule reliability is chosen to minimize total airline and passengers' costs, schedule reliability is highest for direct routing. This explains the superior on- time performance of non-hub carriers such as Southwest Airlines. An example shows that congestion at the hub does not change optimal network design unless delays at the hub are very much larger than at spoke city airports.
TL;DR: In this article, a schedule adjustment device for presenting a time zone candidate for holding a meeting to the participants of the meeting held regularly, it includes: a recording part 16 for recording each behavior information indicating behaviors related to the checked schedule in the respective participants; an operation part 12 to be used for inputting hosts of meeting; a CPU 10 which uses respective schedules corresponding to the respective planned participants and input meeting holding specification data to generate a schedule frequency table and the like indicating a time slot that has possibility to hold the meeting; and a display 13 for notifying an extracted candidate.
Abstract: PROBLEM TO BE SOLVED: To provide a schedule adjustment device enabling respective participants to recognize a time zone where a regular schedule, such as a meeting, can be carried out without adjusting the schedule by actual gathering of the respective participants nor individual contact with the participants. SOLUTION: In the schedule adjustment device for presenting a time zone candidate for holding a meeting to the participants of the meeting held regularly, it includes: a recording part 16 for recording each behavior information indicating behaviors related to the checked schedule in the respective participants; an operation part 12 to be used for inputting hosts of the meeting; a CPU 10 which uses respective schedules corresponding to the respective planned participants and input meeting holding specification data to generate a schedule frequency table and the like indicating a time zone that has possibility to hold the meeting; and a display 13 for notifying an extracted candidate. COPYRIGHT: (C)2009,JPO&INPIT
TL;DR: In this article, a static schedule is used to assign uplink and downlink time to the first client device and associated with each of multiple frames of the base station in a static manner.
Abstract: A technique includes communicating with a base station via a transmitter and a receiver of a first client device based on a static schedule. The static schedule indicates an uplink time and a downlink time allocated to the first client device and associated with each of multiple frames of the base station. Communication time between the base station and multiple client devices linked to the base station including the first client device is divided into multiple frames. A mode request signal is transmitted or received and performs one of: (i) requesting operation in a sleep mode for a selected number S of the frames, and (ii) indicating operation in a standby mode. An initiate signal is transmitted from the first client device to the base station via the transmitter and indicates when to begin operating in the one of the sleep mode and the standby mode.