This doctoral thesis focuses on the modification of ACC to include actual driver workload in the context of automatic headway change. ACC is a driver assistance system that automatically maintains a preliminary defined speed and permits a driver to perform manual headway changes. As drivers show worse (brake) reaction times under high workload situations, the system increases headway accordingly. Driver workload is estimated based on physiological data. Here, we investigate the possibilities of such a system, assuming that physiological sensors can be implemented in future vehicles. The thesis consists of three parts: In the first part, the theoretical background is described and a suitable theoretical model is developed; in the second part, experiments are described, and in the last part, results are discussed. Altogether four experiments support this thesis: 1. The first experiment investigates the foundational relationships between physiology, brake reaction time and workload level. The study employs a simulator setting and results show that physiological data, such as heart rate and skin conductance, permit the identification of different workload levels. These findings validate the results of other studies showing that workload leads to an increase in reaction time. These results could only be validated between the extremes “no-workload” and “high workload” situations. 2. The second experiment simulates an ideal workload-adaptive cruise control (WACC) system. In a simulator setting, system acceptance and awareness are studied, with a view toward future implementation in a real car. The results show better acceptance of WACC in comparison with ACC when subjects receive additional information about the new system. This is because subjects do not perceive changes in distance under high workload conditions. 3. The third experiment focuses on acceptance of the simulated system in on-road conditions. In this study, WACC is integrated in the car and is operated using a MATLAB model. The experiment shows that more subjects notice changes in distance in the on-road condition. In general WACC is preferred over ACC; it is especially these subjects who do not notice changes in distance, who value WACC more than ACC. With the aim of implementing an operational WACC that is capable of adjusting distance according to changes in physiological data, a workload algorithm is developed. 4. The fourth experiment validates the workload algorithm. Results of the algorithm are compared with recordings of the activated workload task and detection rate is calculated. The detection of workload periods was feasible in nearly every case and detection rate was favorable, especially if one considers lags due to design-related latency periods. The experiments presented here indicate that workload is detectable in physiological data and that it influences brake reaction time. Further, we provide evidence pointing to the technical possibility of implementing WACC as well as positive acceptance. The results have been published as an article and are part of this thesis. Also, some parts of the thesis are published as a book chapter (see footnotes). Another publication is in preparation, coauthored by diploma thesis students, who are supervised by the author (consult footnotes). This dissertation is composed, in part, of these publications. References to page numbers of the diploma theses are given to ensure correspondence. The author escorted the topic WACC from the beginning to the end. Sometimes students were involved and intensively supervised, from a thematic as well as a personnel guidance perspective. The author planned the whole project and executed studies and calculations. His psychology insights were not only limited to the discipline of psychology but were furthermore, with the help of students, interdisciplinarily expanded to the subject of informatics. Every study and every result which is presented within this work, was conducted or achieved by the author or (if students supported him) was discussed with the author in weekly discussions (and often several times a day). In these discussions the author provided new ideas and corrections if necessary. Apart from that, the author looked after the fulfillment of the central theme, implemented his psychological knowledge on a daily basis and provided his expertise to complement interdisciplinary point of views. He discussed the central theme as well as details with external partners like the MIT AgeLab as well as professors of the European Union from the adaption project (a project aimed at educating future researchers which includes involvement of highly important commercial and educational partners) and beyond. In this time he also visited conferences and accumulated knowledge which led to the successful achievements of the main objective and he was relevant in reaching the common goals of the adaption project. Furthermore he presented the results of the scientific work on a conference, workshops and in written publications. Within BMW Group Research and Technology, he identified important department- and project- partners and combined the knowledge to a result which benefits science and economy. / In dieser Dissertation wird eine Abwandlung des Active Cruise Control (ACC) untersucht, das zusätzlich die Belastung (Workload) des Fahrers als Parameter betrachtet, um den Abstand zum Vordermann automatisiert zu verändern. Bei diesem ACC handelt es sich um ein Fahrerassistenzsystem, das automatisiert die eingestellte Geschwindigkeit hält und eine manuelle (durch den Nutzer ausgelöste) Abstandsveränderung zum Vordermann ermöglicht. Da sich die Bremsreaktionszeit von Fahrern in hohen Belastungssituationen verschlechtert, soll das entwickelte Workload-adaptive Cruise Control (WACC) in Situationen hoher Belastung den Abstand zum Vordermann automatisiert erhöhen. Die Belastung des Fahrers soll durch physiologische Daten ermittelt werden. Die vorliegende Arbeit untersucht die Möglichkeit eines solchen Systems unter der Annahme, dass in Zukunft geeignete physiologische Sensoren ins Auto eingebaut werden können. Die Arbeit besteht aus drei Teilen: • Im ersten Teil wird der theoretische Hintergrund beschrieben und ein passendes theoretisches Modell entwickelt. • Im zweiten Teil werden die durchgeführten Experimente beschrieben. • Im dritten Teil werden die Ergebnisse diskutiert. Insgesamt wurden im Rahmen dieser Arbeit vier Experimente durchgeführt: Das erste Experiment beschäftigte sich mit den grundlegenden Zusammenhängen zwischen Physiologie, Bremsreaktionszeit und Belastungslevel. Wie die Ergebnisse der im Simulator durchgeführten Studie zeigen, können mit physiologischen Daten wie Herzrate, Herzratenvariabilität und Hautleitfähigkeit unterschiedliche Workloadlevel identifiziert werden. Darüber hinaus wurden die Ergebnisse anderer Studien bestätigt, die belegen, dass Workload die Bremsreaktionszeit erhöht, wobei dies nur im Kontrast zwischen den Extrembereichen „kein Workload“ und „hoher Workload“ nachweisbar ist. Das zweite Experiment diente der Simulierung eines perfekten WACC. Im Simulator wurden Akzeptanz und Systemwahrnehmung getestet, um vor der Implementierung in ein Realfahrzeug weitere Erkenntnisse zu gewinnen. Im Vergleich zum ACC wurde das WACC von den Probanden besser akzeptiert, nachdem sie zusätzliche Informationen zum neuen System erhalten hatten. Der wesentliche Grund dafür ist, dass die Probanden ohne Informationen die Abstandsveränderung bei hohem Workload nicht realisieren. Das dritte Experiment fokussierte auf die Akzeptanz des simulierten Systems unter Realbedingungen. Das WACC wurde in das Auto integriert und durch ein MATLAB Modell gesteuert. Als Ergebnis zeigte sich, dass unter Realbedingungen mehr Probanden die Abstandsveränderung realisieren als im Simulator. Generell wird das WACC präferiert – vor allem jene Probanden, die die Abstandsveränderung nicht realisieren, bewerten das WACC besser als das ACC. Mit den in diesem Teilexperiment erhobenen Daten wurde ein Algorithmus zur Workloaderkennung entwickelt. Auf dieser Basis konnte im letzten Experiment ein Realsystem implementiert werden, das aufgrund physiologischer Daten den Abstand verändert. Das vierte Experiment beschäftigte sich mit der Validierung des Algorithmus zur Workloaderkennung. Die Ergebnisse des Algorithmus wurden mit der aufgezeichneten Aktivierung des Workloadtasks verglichen und eine Detektionsrate ermittelt. Die Detektion der Workloadperioden gelingt in fast allen Fällen und die Detektionsrate ist vielversprechend, gerade wenn man Verzögerungen berücksichtigt, die wegen der Latenzzeit körperlicher Reaktionen nicht verbesserungsfähig sind. In den vorliegenden Experimenten konnte gezeigt werden, dass Workload über die Physiologie messbar ist und sich auf die Bremsreaktionszeit auswirkt. Darüber hinaus wurde gezeigt, dass ein WACC technisch machbar ist und die Ergebnisse lassen außerdem auf eine hohe Akzeptanz schließen. Die Forschungsergebnisse wurden in einem Artikel publiziert, der auch in dieser Dissertation zu finden ist. Teile der vorliegenden Arbeit wurden außerdem als Buchkapitel veröffentlicht (siehe Fußnoten), eine weitere Publikation mit den vom Autor umfassend betreuten Diplomanden ist in Ausarbeitung. Um die Nachvollziehbarkeit zu gewährleisten, wurde auf die Seitenzahlen der entsprechenden Diplomarbeiten verwiesen. Als Autor dieser Dissertation habe ich das Thema WACC von Anfang bis Ende selbst erarbeitet bzw. wurden Studenten eingesetzt und angeleitet, wo es sinnvoll erschien. Neben der fachlichen wie personellen Führung der Studenten umfassten meine Aufgaben die Planung des Gesamtprojekts, das Durchführen der Studien und die Berechnung von Kennzahlen – sowohl in meinem eigenen psychologischen Fachgebiet als auch interdisziplinär mit Hilfe von Experten aus der Informatik. Jedes Ergebnis, das in dieser Arbeit präsentiert wird, wurde entweder von mir selbst erzielt oder – sofern ich dabei von Studenten unterstützt wurde – mit mir in wöchentlichen (oft auch mehrmals täglich stattfindenden Meetings) besprochen. Wichtig war mir als Autor, einen durchgängigen Weg zur Entwicklung eines WACC zu wahren, mein psychologisches Fachwissen täglich anzuwenden und in interdisziplinären Aufgaben und Diskussionen meine Perspektive einzubringen. Besonders wichtig war dabei die Diskussion des Gesamtprojekts und der Details mit externen Partnern wie dem MIT AgeLab oder Professoren aus der Europäischen Union im Rahmen des Adaptation Projekts (ein von der EU gefördertes Projekt zur Ausbildung von Forschern, unter Einbindung wirtschaftlich und wissenschaftlich hochrangiger Partner). Durch die Präsentation der Ergebnisse auf Konferenzen, in Workshops und Publikationen konnte ich einen Beitrag dazu leisten, um die Adaptation-Ziele zu erreichen. Innerhalb der BMW Group Forschung und Technik habe ich darauf geachtet, relevante Schnittstellen- und Projektpartner zu identifizieren und das erlangte Wissen zu einem Ergebnis zu verbinden, das Wissenschaft und Wirtschaft gleichermaßen nützt.

Server consolidation is currently widely employed in order to improve the energy efficiency of data centers. While being a promising technique, server consolidation may lead to resource interference between applications and thus, reduced performance of applications. Current approaches to account for possible resource interference are not well suited to respect the variation in the workloads for the applications. As a consequence, these approaches cannot prevent resource interference if workload for applications vary. It is assumed that having models for the resource utilization and power consumption of applications as functions of the workload to the applications can improve decision making and help to prevent resource interference in scenarios with varying workload. This thesis aims to develop such models for selected applications. To produce varying workload that resembles statistical properties of real-world workload a workload generator is developed in a first step. Usually, the measurement data for such models origins from different sensors and equipment, all producing data at different frequencies. In order to account for these different frequencies, in a second step this thesis particularly investigates the feasibility to employ quantile functions as model inputs. Complementary, since conventional goodness-of-fit tests are not appropriate for this approach, an alternative to assess the estimation error is presented. / Serverkonsolidierung wird derzeit weithin zur Verbesserung der Energieeffizienz von Rechenzentren eingesetzt. Während diese Technik vielversprechende Ergebnisse zeitigt, kann sie zu Ressourceninterferenz und somit zu verringerter Performanz von Anwendungen führen. Derzeitige Ansätze, um dieses Problem zu adressieren, sind nicht gut für Szenarien geeignet, in denen die Workload für die Anwendungen variiert. Als Konsequenz daraus folgt, dass diese Ansätze Ressourceninterferenz in solchen Szenarien nicht verhindern können. Es wird angenommen, dass Modelle für Anwendungen, die deren Ressourenauslastung und die Leistungsaufnahme als Funktion der Workload beschreiben, die Entscheidungsfindung bei der Konsolidierung verbessern und Ressourceninterferenz verhindern können. Diese Arbeit zielt darauf ab, solche Modelle für ausgewählte Anwendungen zu entwickeln. Um variierende Workload zu erzeugen, welche den statistischen Eigenschaften realer Workload folgt, wird zunächst ein Workload-Generator entwickelt. Gewöhnlicherweise stammen Messdaten für die Modelle aus verschienenen Sensoren und Messgeräten, welche jeweils mit unterschiedlichen Frequenzen Daten erzeugen. Um diesen verschiedenen Frequenzen Rechnung zu tragen, untersucht diese Arbeit insbesondere die Möglichkeit, Quantilfunktionen als Eingabeparameter für die Modelle zu verwenden. Da konventionelle Anpassungsgütetests bei diesem Ansatz ungeeignet sind, wird ergänzend eine Alternative vorgestellt, um den durch die Modellierung entstehenden Schätzfehler zu bemessen.

The focus of this field investigation was an analysis of the work demands being placed on South African forestry workers, in particular Chainsaw Operators and Stackers. Working postures, physiological and perceptual responses were assessed on a sample of 58 workers (29 Chainsaw Operators and 29 Stackers) during a ‘normal’ working shift. Body mass was measured before and after work in order to determine dehydration levels. Polar heart rate monitors were fitted to six workers each day over a period of two weeks in order to record ‘working’ heart rates. Fluid and food intake was monitored and recorded during this initial data collection phase. The Rating of Perceived Exertion and Body Discomfort Scales were explained in Zulu, their native language, and workers were asked to rate their perceptions of effort at regular intervals during work, while areas and intensity of body discomfort was obtained on completion of work. After completing a work shift, a 30 minute ‘recovery’ period was given, thereafter a portable ergospirometer, the k4b², was attached to the worker who then participated in a progressive, submaximal step test for the purpose of establishing individual, and group, heart rate-oxygen uptake (HR/VO[subscript 2]) regressions for predicting oxygen uptake from ‘working’ heart rate responses. These procedures were repeated four weeks later following the introduction of a fluid and nutritional supplement during work which was delivered to the workers while they were executing their tasks. The results revealed awkward working postures with a predominance of trunk flexion during all the harvesting tasks; these postures, adopted for long periods during work, are very likely to lead to the development of musculoskeletal injuries. The mean working heart rates were 123.3 bt.min[superscript (-1)] and 117.6 bt.min[superscript (-1)] during chainsaw operations and stacking respectively. During the step test, the mean heart rate and oxygen uptake responses were 127.9 bt.min[superscript (-1)] and 22.9 mlO[subscript 2].kg[superscript (-1)].min[superscript (-1)] (Chainsaw Operators) and 116.9 bt.min[superscript (-1)] and 24.0 mlO[subscript 2].kg[superscript (-1)].min[superscript (-1)] (Stackers), revealing no significant difference between the ‘working’ heart rates and the heart rates recorded during the step test. Physiological responses were analyzed over the full work shift which was divided into four quarters. Heart rate and oxygen uptake were significantly higher during the last half of the Chainsaw Operators’ work shift compared to the first half. Heart rate increased from 120.7 bt.min[superscript (-1)] during the first quarter to 127.4 bt.min[superscript (-1)] during the last quarter of chainsaw operations. Likewise, oxygen uptake increased from 19.9 mlO[subscript 2].kg[superscript (-1)].min[superscript (-1)] to 22.9 mlO[subscript 2].kg[superscript (-1)].min[superscript (-1)] from the first to the last quarter of work. During stacking the heart rate (mean of 117.6 bt.min[superscript (-1)]) and oxygen uptake (mean of 24.6 ml.kg[superscript (-1)].min[superscript (-1)]) responses remained stable over the duration of the working shift. Workers lost, on average, 2.8% body mass during work while felling and cross-cutting and 3.6% during stacking. This reduced significantly to a loss of 0.4% body mass when re-tested following the introduction of water and food during the work period. Likewise, the energy deficit was significantly improved due to the introduction of a nutritional supplement. Pre-intervention the deficit was 8861.8 kJ (Chainsaw Operators) and 8804.2 kJ (Stackers) while in the post-intervention phase this deficit was reduced by approximately 50% for both groups of workers.

A scheduler, as a central components of a computing site, aggregates computing resources and is responsible to distribute the incoming load (jobs) between the resources. Under such an environment, the optimum performance of the system against the service level agreement (SLA) based workloads, can be achieved by calculating the priority of SLA bound jobs using integrated heuristic. The SLA defines the service obligations and expectations to use the computational resources. The integrated heuristic is the combination of different SLA terms. It combines the SLA terms with a specific weight for each term. Theweights are computed by applying parameter sweep technique in order to obtain the best schedule for the optimum performance of the system under the workload. The sweepingof parameters on the integrated heuristic observed to be computationally expensive. The integrated heuristic becomes more expensive if no value of the computed weights result in improvement in performance with the resulting schedule. Hence, instead of obtaining optimum performance it incurs computation cost in such situations. Therefore, there is a need of detection of situations where the integrated heuristic can be exploited beneficially. For that reason, in this thesis we propose a metric based on the concept of utilization, to evaluate the SLA based parallel workloads of independent jobs to detect any impact of integrated heuristic on the workload.

De tekniska system som tävlar om förarens uppmärksamhet i bilar och lastbilar ökar både i antal och komplexitet. Detta kanske inte är ett problem på en rak, lugn motorväg men minskar fokus på själva körningen och om något oväntat skulle hända kan konsekvenserna bli allvarliga eftersom föraren är distraherad och kan behöva ta in för mycket information på en gång. Syftet med projektet var att utveckla ett system för att presentera endast relevant och önskad information till förare av lastbilar och bussar i kritiska trafiksituationer. Detta för att göra det möjligt för föraren att fokusera mer på körningen och därigenom göra den säkrare och bekvämare. Å ena sidan ska systemet upptäcka vilken typ av trafiksituation lastbilen befinner sig i. Å andra sidan ska det avgöra vilken typ av information som skulle vara relevant för föraren i den situationen. Med en litteraturstudie, insamlad statistik, intervjuer och författarnas åsikter som grund identifierades ett antal händelser (som telefonsamtal och förekommande varningar) som kan inträffa i förarhytten på en lastbil och hur mycket de vardera skulle öka förarens arbetsbörda (workload). Detsamma gjordes för ett antal vanliga trafiksituationer som kan betraktas som kritiska och kräver mer uppmärksamhet än att bara köra rakt fram. Dessa händelser och situationer betygsattes därefter utifrån hur mycket de skulle öka belastningen på de sinnen som används mest i en körsituation, nämligen: synen, hörseln, motoriken och kognitionen. Matriser gjordes i vilka uppgifter och situationer ställdes mot varje sinne med betyg vilket senare användes som grund för de tre koncept som utvecklades för systemet. Koncepten hette Jigsaw, Fever och Three’s a crowd och utvärderades i en workshop på Scania. De två första realiserades i form av prototyper som gjordes i programmet GUIDE. Logiken som byggdes upp i programmet bestod av tillståndsmaskiner och med boolsk logik samt if- och while-slingor. / The technical systems that compete for drivers’ attention in cars and trucks are increasing both in numbers and complexity. This may not be a problem on a straight and sound highway but definitely decreases the focus on the actual driving and if something unexpected was to happen there could be dangerous consequences, due to too much distraction and information overload. The purpose of the project was to develop a system to present only relevant and desired information to drivers of trucks and busses in critical traffic situations, for the Swedish truck manufacturer Scania. This will enable the driver to focus more on the driving thus creating a safer and more comfortable driving situation. On one hand the system had to detect what type of traffic situation the truck is in. On the other hand it had to determine what type of information would be suitable for the driver in that situation. With a literature study, statistics, interviews and the authors’ judgments as a basis the project first identified a number of tasks (like phone calls and occurring warnings) that can take place in the cab of a truck and then assess how much they respectively would raise the workload of the driver. The same was done for a number of common traffic situations that were considered as critical and demanded more attention than just driving straight ahead. All these tasks and situations were graded on how much they would raise the load on the senses most used in a driving situation: visual, auditory, motor and cognitive. Matrices were made cross-referencing the tasks and situations with the grades on each modality and was used as the basis for the three concepts for the system that was developed. The concepts called Jigsaw, Fever and Three’s a crowd were evaluated in a workshop at Scania and the first two were realized in the form of prototypes which were made in the software GUIDE. The logic was made up of state machines and Boolean operators and if- and while-conditions.

The objective of this study was to assess low to high levels of Cognitive Workload by measuring heart rate and cortical blood flow in real-time. Four conditions were implemented into a within-subjects experimental design. Two conditions of difficulty and two conditions of trial order were used to illicit different levels of workload which will be analyzed with psychophysiological equipment. Functional Near-Infrared Spectroscopy (fNIRS) has become more prominent for measuring the blood oxygenation levels in the prefrontal cortex of individuals operating in hazardous work environments, students with learning disabilities, and in research for military training. This is due to the fNIR device being highly mobile, inexpensive, and able to produce a high-spatial resolution of the dorsolateral prefrontal cortex during executive functioning. Heart Rate will be measured by an Electrocardiogram, which will be used in concordance with fNIR oxygenation levels to predict if an individual is in a condition that produces low or high mental workload. Successfully utilizing heart rate and blood oxygenation data as predictors of cognitive workload may validate implementing multiple physiological devices together in real-time and may be a more accurate solution for preventing excessive workload.

No description available.

Apache Hadoop is an open source framework that delivers reliable, scalable, and distributed computing. Hadoop services are provided for distributed data storage, data processing, data access, and security. MapReduce is the heart of the Hadoop framework and was designed to process vast amounts of data distributed over a large number of nodes. MapReduce has been used extensively to process structured and unstructured data in diverse fields such as e-commerce, web search, social networks, and scientific computation. Understanding the characteristics of Hadoop MapReduce workloads is the key to achieving improved configurations and refining system throughput. Thus far, MapReduce workload characterization in a large-scale production environment has not been well studied. In this thesis project, the focus is mainly on composing a Hadoop cluster (as an execution environment for data processing) to analyze two types of Hadoop MapReduce (MR) jobs via a proposed coordination framework. This coordination framework is referred to as a workload translator. The outcome of this work includes: (1) a parametric workload model for the target MR jobs, (2) a cluster specification to develop an improved cluster deployment strategy using the model and coordination framework, and (3) better scheduling and hence better performance of jobs (i.e. shorter job completion time). We implemented a prototype of our solution using Apache Tomcat on (OpenStack) Ubuntu Trusty Tahr, which uses RESTful APIs to (1) create a Hadoop cluster version 2.7.2 and (2) to scale up and scale down the number of workers in the cluster. The experimental results showed that with well tuned parameters, MR jobs can achieve a reduction in the job completion time and improved utilization of the hardware resources. The target audience for this thesis are developers. As future work, we suggest adding additional parameters to develop a more refined workload model for MR and similar jobs. / Apache Hadoop är ett öppen källkods system som levererar pålitlig, skalbar och distribuerad användning. Hadoop tjänster hjälper med distribuerad data förvaring, bearbetning, åtkomst och trygghet. MapReduce är en viktig del av Hadoop system och är designad att bearbeta stora data mängder och även distribuerad i flera leder. MapReduce är använt extensivt inom bearbetning av strukturerad och ostrukturerad data i olika branscher bl. a e-handel, webbsökning, sociala medier och även vetenskapliga beräkningar. Förståelse av MapReduces arbetsbelastningar är viktiga att få förbättrad konfigurationer och resultat. Men, arbetsbelastningar av MapReduce inom massproduktions miljö var inte djup-forskat hittills. I detta examensarbete, är en hel del fokus satt på ”Hadoop cluster” (som en utförande miljö i data bearbetning) att analysera två typer av Hadoop MapReduce (MR) arbeten genom ett tilltänkt system. Detta system är refererad som arbetsbelastnings översättare. Resultaten från denna arbete innehåller: (1) en parametrisk arbetsbelastningsmodell till inriktad MR arbeten, (2) en specifikation att utveckla förbättrad kluster strategier med båda modellen och koordinations system, och (3) förbättrad planering och arbetsprestationer, d.v.s kortare tid att utföra arbetet. Vi har realiserat en prototyp med Apache Tomcat på (OpenStack) Ubuntu Trusty Tahr som använder RESTful API (1) att skapa ”Hadoop cluster” version 2.7.2 och (2) att båda skala upp och ner antal medarbetare i kluster. Forskningens resultat har visat att med vältrimmad parametrar, kan MR arbete nå förbättringar dvs. sparad tid vid slutfört arbete och förbättrad användning av hårdvara resurser. Målgruppen för denna avhandling är utvecklare. I framtiden, föreslår vi tilläggning av olika parametrar att utveckla en allmän modell för MR och liknande arbeten.

The purpose of this study is to document how much time teachers in a large suburban school district expend on their professional responsibilities at home and at school. The study also documents the time usage and allocation through the relationships of teaching experience and teaching grade level assignment. Fairfax County Public Schools and all school systems are facing increasing demands for educational reform. Teacher responsibilities have continued to increase with many current reform initiatives. Consequently the associated time for reform implementation, with increased demands is not limitless. Current time usage documentation is important data needed in future educational reform decisions. Two hundred and thirty-one randomly selected teachers completed a questionnaire regarding the time spent working in an average week for Fairfax County Public Schools. The results of this study are reported in total time spent on tasks associated with their professional responsibility both at home and school; and time spent specifically on; individual planning, group/team planning, assessment, instructional contact, career and staff development and parent communication. The mean hours per week reported in this survey was fifty-nine hours per week. T-Tests comparisons revealed Significant differences in three categories at the .10 level of confidence; first year teachers spend less time in staff development, middle school teachers spend more time in team planning and elementary teachers spend less time in team planning. There were no significant findings in any other areas of data analysis. T-Tests were utilized to examine Significant differences in time distribution between means in the following demographic areas; years of teaching experience and grade level assignment. Reviews of literature reveal a few studies of teacher time documentation exist in England and West Germany. This study is one of the first in the United States documenting teacher time usage in a large suburban school district. The interpretive results from this study provide data for strategic planning for educational reform and suggest areas for further research in teacher time usage. / Ed. D.

Recent developments in the area of Cyber-Physical Production Systems prove that high technology readiness level is already achieved and industrialization of such technologies is not far from today. Although these technologies seem to be convenient in providing solutions to environmental uncertainties, their application provides adaptability only at shop floor level. Needless to say, an enterprise cannot reach true adaptability without ensuring adaptation skills at every level in its hierarchy. Commonly used production planning and control approaches in industry today inherit from planning solutions which are developed in response to historical market characteristics. However, market tendency in recent years is towards making personalized products a norm. The emerging complexity out of this trend obliges planning systems to a transition from non-recurring, static planning into continuous re-planning and re-configuration of systems. Therefore, there is a need of responsive planning solutions which are integrated to highly adaptable production system characteristics. In this dissertation, Demand Responsive Planning, DRP, is presented which is a planning framework aiming to respond to planning needs of shifting trends in both production system technologies and market conditions. The DRP is based on three main constructs such as dynamicity, responsiveness and use of precise data. These features set up the foundation of accomplishing a high degree of adaptability in planning activities. By this means, problems from an extensive scope can be handled with a responsive behavior (i.e. frequent re-planning) by the use of precise data. The use of precise data implies to execute planning activities subject to actual demand information and real-time shop floor data. Within the context of the DRP, both a continuous workload control method and a dynamic capacity adjustment approach are developed. A test-bed is coded in order to simulate proposed method based on a system emulation reflecting the characteristics of cyber-physical production systems at shop floor level. Continuous Precise Workload Control, CPWLC, method is a novel approach aiming at precise control of workload levels with the use of direct load graphs. Supported by a multi-agent platform, it generates dynamic non-periodic release decisions exploiting real time shop floor information. As a result, improved shop floor performances are achieved through controlling workload levels precisely by the release of appropriate job types at the right time. Presented dynamic capacity adjustment approach utilizes rapid re-configuration capability of cyber-physical systems in achieving more frequent capacity adjustments. Its implementation architecture is integrated to the CPWLC structure. By this means, a holistic approach is realized whereby improved due date performance is accomplished with minimized shop floor congestion. Hence, sensitivity to changing demand patterns and urgent job completions is improved. / <p>QC 20150907</p>