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In the 1980s and 1990s, publications like A Nation at Risk and Prisoners of Time were highly critical of the American public school system. In response, school administrators reviewed their master schedules to evaluate how time was scheduled and the majority of them chose block scheduling to secure longer, uninterrupted periods of instructional time. Upon implementing block scheduling, schools noted a need for a change in pedagogy. Constructivist teaching, shown to be effective with multiple ages, has become a preferred pedagogy for elementary and middle school teachers during a block period. The review of literature includes a description of the forces behind block scheduling and provides a background of constructivist theory and teaching practices based on the writings of Jean Piaget and Lev Vygotsky. Combining constructivist teaching with block scheduling creates an environment conducive to young adolescent learning; however, properly preparing teachers through professional development is key to effective implementation. The purpose of this action research study was to facilitate the professional growth of new teachers by providing job embedded professional development opportunities that were grounded in constructivist practices and demonstrated to be effective with young adolescent learners while teaching in a block period. / Ed. D.

Educators across the nation are rethinking the organization of the high school day in relation to time as they face the challenges of a new century. Block scheduling, the use of extended periods of time for learning, is one response to the reorganization of the high school where in Virginia during the 2000-2001 school year, 74% of the high schools were on some form of block scheduling. Two models of block scheduling continue to receive attention in the review of educational literature. They are the alternating day or A-B model and the 4 x 4 model. Although there are numerous qualitative research studies regarding the effects of block scheduling on school climate and student achievement, there is limited quantitative evidence that supports the use of block scheduling to improve student academic achievement on criterion-referenced standardized test scores. This study compared the effects of the 7-period alternating day schedule, the 4 x 4 block schedule, and the traditional single-period schedule on high school student academic achievement as measured by the Virginia Stanards of Learning (SOL) end-of-course assessments. An Analysis of Variance was used as the primary tool to test for mean differences between the test scores. The results indicated that the mean scaled scores for the 7-period alternating day were significantly higher (p<.05) than the mean scaled scores for the 4 x 4 block on the English:Reading, English:Writing, and geometry SOL end-of-course tests. In addition, the mean scaled scores for the 7-period alternating day and the traditional schedule were significantly higher (p<.05) than the 4 x 4 block on the English:Writing SOL end-of-course tests. It appears that the 7-period alternating day schedule has merit in terms of English and geometry instruction. Division and school leaders will want to explore the effects of the 7-period alternating day schedule on English and geometry courses. As a new century unravels, the question of time and how it is used for student learning will continue to be a major focus. Educational leaders must continue to work together with teachers to design and to develop a high school schedule that will provide a maximum learning experience for all students. / Ed. D.

The Critical Path Method (CPM) is a widely used tool throughout the construction industry. Since its creation, the use and application of the Critical Path Method has grown tremendously. Up to date, three studies have been performed on how Engineering News Record's (ENR) Top 400 Contractor use CPM. The first study was performed by Edward Davis in 1974 and the second was performed by Amir Tavakoli and Roger Riachi in 1990. This paper is a summary of the third survey, which took place in 2003. The results from the three studies indicate that CPM use by the Top 400 Contractors is growing and the areas of use are expanding. The number one use of CPM throughout the years is detailed planning before the start of construction. Periodic control during construction is another large area of CPM use and has been a large area of growth due to the advances in technology, which make updating a schedule during construction easier and faster than was possible with a mainframe computer in the past. Another area of CPM growth is estimating and bidding for several reasons: use in this area has jumped from 19% to 54% in the past 30 years. An area of concern lately in CPM is the use of precedence diagramming instead of arrow diagramming. Despite the debate, the responding companies found precedence diagrams easier to read, provide more flexibility, and allow for easier use of "smart" relationships (i.e. start-start). / Master of Science

In this dissertation, we consider timeliness and energy optimization in battery-powered, mobile embedded real-time systems. We focus on real-time systems that operate in environments with dynamically uncertain properties, including context-dependent activity execution times and arbitrary activity arrival patterns. We consider an application model where activities are subject to time/utility function (or TUF) time constraints, mutual exclusion constraints on concurrent sharing of non-CPU resources, timeliness requirements including assurances on individual activity timeliness behavior, and system-level energy consumption requirements including a non-exhaustable energy budget. To account for uncertainties in activity properties in dynamic systems, we stochastically describe activity execution demands, and describe activity arrival behaviors using the unimodal arbitrary arrival model, which allows unbounded arrival frequencies. We consider the scheduling optimality criteria of: (1) probabilistically satisfying lower bounds on individual activities' maximal timeliness utilities, and (2) maximizing system-level energy efficiency, while ensuring that the system's energy consumption never exhausts the energy budget and resource mutual exclusion constraints are satisfied. For this multi-criteria scheduling problem, we present a DVS (dynamic voltage scaling)-based, real-time scheduling algorithm called the Energy-Bounded Utility Accrual Algorithm (or EBUA). Since the scheduling problem is NP-hard, EBUA heuristically (and dynamically) allocates CPU cycles to activities, computes activity schedules, and scales CPU voltage and frequency with a polynomial-time cost. If activities' cumulative execution demands exceed the available CPU time or may exhaust the system's energy budget, the algorithm defers and rejects jobs in a controlled fashion, minimizing system-level energy consumption and maximizing total accrued utility. We analytically establish several properties of EBUA. We prove that the algorithm never exhausts the specified energy budget. Further, we establish EBUA's timeliness optimality during under-loads, freedom from deadlocks, and correctness in mutually exclusive resource sharing. In particular, we prove that the algorithm's timeliness behavior subsumes the optimal timeliness behavior of deadline scheduling as a special case, and identify the conditions under which lower bounds on individual activity utilities are satisfied. In addition, we upper bound the time needed for mutually exclusively accessing shared resources under EBUA. We conduct experimental studies by simulating the algorithm on the DVS-enabled AMD k6 processor model, and by implementing it on QNX Neutrino 6.2.1 RTOS. Our experimental results validate our analytical results. Further, they confirm EBUA's superiority over other energy-efficient real-time scheduling algorithms on timeliness and energy consumption behaviors. / Ph. D.

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This work focuses on scheduling of MPI jobs when executing in shared-memory multiprocessors (SMPs). The objective was to obtain the best performance in response time in multiprogrammed multiprocessors systems using batch systems, assuming all the jobs have the same priority. To achieve that purpose, the benefits of supporting malleability on MPI jobs to reduce fragmentation and consequently improve the performance of the system were studied. The contributions made in this work can be summarized as follows:· Virtual malleability: A mechanism where a job is assigned a dynamic processor partition, where the number of processes is greater than the number of processors. The partition size is modified at runtime, according to external requirements such as the load of the system, by varying the multiprogramming level, making the job contend for resources with itself. In addition to this, a mechanism which decides at runtime if applying local or global process queues to an application depending on the load balancing between processes of it. · A job scheduling policy, that takes decisions such as how many processes to start with and the maximum multiprogramming degree based on the type and number of applications running and queued. Moreover, as soon as a job finishes execution and where there are queued jobs, this algorithm analyzes whether it is better to start execution of another job immediately or just wait until there are more resources available. · A new alternative to backfilling strategies for the problema of window execution time expiring. Virtual malleability is applied to the backfilled job, reducing its partition size but without aborting or suspending it as in traditional backfilling. The evaluation of this thesis has been done using a practical approach. All the proposals were implemented, modifying the three scheduling levels: queuing system, processor scheduler and runtime library. The impact of the contributions were studied under several types of workloads, varying machine utilization, communication and, balance degree of the applications, multiprogramming level, and job size. Results showed that it is possible to offer malleability over MPI jobs. An application obtained better performance when contending for the resources with itself than with other applications, especially in workloads with high machine utilization. Load imbalance was taken into account obtaining better performance if applying the right queue type to each application independently.The job scheduling policy proposed exploited virtual malleability by choosing at the beginning of execution some parameters like the number of processes and maximum multiprogramming level. It performed well under bursty workloads with low to medium machine utilizations. However as the load increases, virtual malleability was not enough. That is because, when the machine is heavily loaded, the jobs, once shrunk are not able to expand, so they must be executed all the time with a partition smaller than the job size, thus degrading performance. Thus, at this point the job scheduling policy concentrated just in moldability.Fragmentation was alleviated also by applying backfilling techniques to the job scheduling algorithm. Virtual malleability showed to be an interesting improvement in the window expiring problem. Backfilled jobs even on a smaller partition, can continue execution reducing memory swapping generated by aborts/suspensions In this way the queueing system is prevented from reinserting the backfilled job in the queue and re-executing it in the future.

Partitioned preemptive EDF scheduling is very similar to bin packing, but there is a subtle difference. Estimating the probability of schedulability under a given total utilization has been studied empirically before. Here, we show an approach for closed-form formulae for the problem, starting with n = 3 tasks on m = 2 processors.

The objective of this thesis is to introduce MES systems with their properties and relations to other automation systems. Furthermore production scheduling theory is introduced with applicable mathematical methods. For given scheduling problem is created optimization model and basic serie of simulations is accomplished. The core of an existing MES system is transformed to web non-comercial platform. All necessary changes are listed in order to integrate production scheduling subsystem to the existing MES system.

The task of scheduling mining operations is a strikingly tough task yet it is still largely done manually by hand or with the help of simple gantt planning tools. This thesis aim is to explore the feasibility of an automatic scheduling solution that can incorporate the constraints specific to mining operations. A constraint programming based solution is presented and evaluated based on its correctness, viability and performance. With its rich set of operators, the constraint programming library OR-Tools is able to capture most of the mining specific constraints and two different objective functions are developed to suit different use cases. One is the well established makespan objective which purpose is to minimize the completion time of the last task. The second objective function, named the sub goal deviation objective, minimizes the deviation from the overall production goal divided into sub goals.  The underlying scheduling problem is notoriously hard to solve optimally for large instances. This is supported by several related studies and also by experimental results. To mitigate the performance degradation for large scheduling instances, an iterative solver strategy is presented. With this strategy the scheduler is able to solve much larger instances and initial tests resulted in the same objective values as the optimal strategy. A rescheduling procedure is presented to support schedule maintenance due to unforeseen circumstances such as delays or machine breakdowns. It is concluded that automatic scheduling and rescheduling is feasible but that it first needs to be evaluated by experienced schedulers in the field before being applied in a production environment.