The Establishment of a Student Self-Scheduling System at Greenville High School

The purpose of this study is to explain the mechanics involved with a scheduling system which will reduce student schedule changes and promote a smoother start to the academic school year. The study will not only trace the history of self-scheduling at Effingham High School beginning in 1975 but will outline the method used to continue a similar scheduling system at Greenville High School in 1978. As a guidance counselor at Effingham High School starting in the school year of 1974, I was dissatisfied with the scheduling system. Not surprisingly, the other two guidance personnel plus most of the teaching staff did not care for the present system. The number of schedule changes were about one-third of the total enrollment of the school. As an assistant principal at Greenville High School starting in the school year of 1977, I found that the Guidance Department plus many of the teachers did not like their scheduling system. Although both scheduling systems are basically the same at both schools, my role in the promotion of self-scheduling had changed. At Effingham, the principal had to be convinced so he would speak on behalf of self-scheduling to the school board. At Greenville, I was asked by the superintendent to convince the school board of the worth of this system. The key to both approvals was convincing the school boards of the respective districts to try a new idea that is not used extentsively in a high school setting. Although colleges almost exclusively use a slight variation of self-scheduling, high schools for the most part have not adopted it. Giving a high school student this responsibility changes his attitude towards the courses he must take because he will have optional times for class and teacher selection. The pre-registration and forms that are used are similar to many high school schedules now is existence. The contruction of a schedule, if a computer is used, is still traditionally done by using a conflict matrix to try and provide as many first choices for classes as any other system. The difference comes when actual registration takes place. The students are supplied with a computer printout schedule that works plus a listing of all class times and the teachers for each section. This information is mailed approximately 10 days before registration. The registration takes place about one week before the school year actually begins. They are told in the mailing that this schedule works but if they want to change the time a given class is scheduled or the teacher that is involved, they may do so at their time of registration if room is available. Limits of seating are set so one class of a section is not overloaded. At the end of registration, all classes will be fairly balanced. Seniors go first for one-half day, then the underclassmen follow. The alphabet is rotated so no specific last name of a student will be an advantage. Each grade is divided into six sections and their sizes range from 25 to 32. A student cannot register before his assigned time but can register later. In my involment with this type of scheduling, 95% of the students or more arrive at the specific time designated. The study concludes by comparing a computerized scheduling with self-scheduling. The humanizing factor of self-scheduling will cut down on schedule changes because that is what the student had already been invited to do: change his schedule. The school year will start in better fashion because the guidance personnel are not faced with long lines for changes. Self-scheduling gives the student a responsibility to decide which hours he will take certain classes. The student, and the staff members, also become more aware of the complexities of schedule making

USEM: A ubiquitous smart energy management system for residential homes

With the ever-increasing worldwide demand for energy, and the limited available energy resources, there is a growing need to reduce our energy consumption whenever possible. Therefore, over the past few decades a range of technologies have been proposed to assist consumers with reducing their energy use. Most of these have focused on decreasing energy consumption in the industry, transport, and services sectors. In more recent years, however, growing attention has been given to energy use in the residential sector, which accounts for nearly 30% of total energy consumption in the developed countries. Here we present one such system, which aims to assist residential users with monitoring their energy usage and provides mechanisms for setting up and controlling their home appliances to conserve energy. We also describe a user study we have conducted to evaluate the effectiveness of this system in supporting its users with a range of tools and visualizations developed for ubiquitous devices such as mobile phones and tablets. The findings of this study have shown the potential benefits of our system, and have identified areas of improvement that need to be addressed in the future

Adaptive Transactional Memories: Performance and Energy Consumption Tradeoffs

Energy efficiency is becoming a pressing issue, especially in large data centers where it entails, at the same time, a non-negligible management cost, an enhancement of hardware fault probability, and a significant environmental footprint. In this paper, we study how Software Transactional Memories (STM) can provide benefits on both power saving and the overall applications’ execution performance. This is related to the fact that encapsulating shared-data accesses within transactions gives the freedom to the STM middleware to both ensure consistency and reduce the actual data contention, the latter having been shown to affect the overall power needed to complete the application’s execution. We have selected a set of self-adaptive extensions to existing STM middlewares (namely, TinySTM and R-STM) to prove how self-adapting computation can capture the actual degree of parallelism and/or logical contention on shared data in a better way, enhancing even more the intrinsic benefits provided by STM. Of course, this benefit comes at a cost, which is the actual execution time required by the proposed approaches to precisely tune the execution parameters for reducing power consumption and enhancing execution performance. Nevertheless, the results hereby provided show that adaptivity is a strictly necessary requirement to reduce energy consumption in STM systems: Without it, it is not possible to reach any acceptable level of energy efficiency at all