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We optimize parameters in OpenACC clauses for a stencil evaluation kernel executed on Graphical Processing Units (GPUs) using a variety of machine learning and optimization search algorithms, individually and in hybrid combinations, and compare execution time performance to the best possible obtained from brute force search. Several auto-tuning techniques – historic learning, random walk, simulated annealing, Nelder-Mead, and genetic algorithms – are evaluated over a large two-dimensional parameter space not satisfactorily addressed to date by OpenACC compilers, consisting of gang size and vector length. A hybrid of historic learning and Nelder-Mead delivers the best balance of high performance and low tuning effort. GPUs are employed over an increasing range of applications due to the performance available from their large number of cores, as well as their energy efficiency. However, writing code that takes advantage of their massive fine-grained parallelism requires deep knowledge of the hardware, and is generally a complex task involving program transformation and the selection of many parameters. To improve programmer productivity, the directive-based programming model OpenACC was announced as an industry standard in 2011. Various compilers have been developed to support this model, the most notable being those by Cray, CAPS, and PGI. While the architecture and number of cores have evolved rapidly, the compilers have failed to keep up at configuring the parallel program to run most e ciently on the hardware. Following successful approaches to obtain high performance in kernels for cache-based processors using auto-tuning, we approach this compiler-hardware gap in GPUs by employing auto-tuning for the key parameters “gang” and “vector” in OpenACC clauses. We demonstrate results for a stencil evaluation kernel typical of seismic imaging over a variety of realistically sized three-dimensional grid configurations, with different truncation error orders in the spatial dimensions. Apart from random walk and historic learning based on nearest neighbor in grid size, most of our heuristics, including the one that proves best, appear to be applied in this context for the first time. This work is a stepping-stone towards an OpenACC auto-tuning framework for more general high-performance numerical kernels optimized for GPU computations.

A hallmark of higher-order cortical regions is their functional heterogeneity, but it is not well understood how these areas are able to encode diverse behavioral information. The anterior cingulate cortex (ACC), for example, is known to be important in a large range of behaviors, including, decision making, emotional regulation and social cognition. In support of this, previous work shows activation of the ACC to anxiety-related and social stimuli but does not use cellular resolution or cell-type specific techniques to elucidate the possible heterogeneity of its subcircuits. In this work, I investigate how subpopulations of neurons or microcircuits within the ACC encode these different kinds of stimuli. One type of inhibitory interneuron, which is positive for vasoactive intestinal peptide (VIP), is known to alter the activity of clusters of pyramidal excitatory neurons, often by inhibiting other types of inhibitory cells. Prior to this research, it was unknown whether the activity of VIP cells in the ACC (VIPACC) encodes anxiety-related or social information and whether all VIPACC activate similarly to the same behavioral stimuli. Using in vivo Ca2+ imaging and 3D-printed miniscopes in freely behaving mice to monitor VIPACC activity, I have identified distinct subpopulations of VIPACC that preferentially activate to either anxiogenic, anxiolytic, social, or non-social stimuli. I also demonstrate that these stimulus-selective subpopulations are largely non-overlapping and that clusters of cells may co-activate, improving their encoding. Finally, I used trans-synaptic tracing to map monosynaptic inputs to VIP and other interneuron subtypes in the ACC. I found that VIPACC receive widespread inputs from regions implicated in emotional regulation and social cognition and that some inputs differ between types of ACC interneurons. Overall, these data demonstrate that the ACC is not homogeneous – there is marked functional heterogeneity within one interneuron population in the ACC and connective heterogeneity across ACC cell types. This work contributes to our broader understanding of how the cortex encodes information across diverse contexts and provides insight into the complexity of neural processes involved in anxiety and social behavior.

Magister Philosophiae - MPhil / This study deals with the evaluation research conducted to evaluate the Accounting curriculum of Asmara Commercial College (ACC), Eritrea. The purpose of the Accounting programme in this college is to train middle level skilled manpower to satisfy the dire shortages of Accounting personnel in the country. Accounting education in Eritrea seems to lag behind the rest of the world, particularly in curriculum administration and development aspects of the discipline. The target group of the above programme was directed to the 11th grade candidates who have passed the matriculation exam. The primary goal of this training was to achieve qualified students and help them to prepare for the world of work at the end of the programme. A second goal was to assist them in their professional development as future accountants. The study therefore evaluated how successfully the Accounting curriculum helped the students to develop themselves academically and professionally. It was also aimed at providing some suggestions and recommendations to the curriculum developers and teachers of the college in particular and other interested parties to assist them in identifying different aspects of the object of evaluation questions to be addressed. The researcher used both a literature review and empirical data to achieve the desired aim. Based on the literature, the Accounting education concepts, the concepts of change and evaluation as well as the role of evaluation in relation to the Accounting curriculum had been reviewed in order to support the study with its theoretical background. In the empirical part of the study, it investigated the perceptions of the respondents concerning the current Accounting practice at ACC and its relationship with the world of work. The necessary empirical data were mainly collected by 1) interviews and 2)-document analysis. The respondents were seven: 1) the director of ACC, 2) two Accounting instructors from ACC, 3) two employers, and 4) two graduates students. A normal flow of text had been used to analyze each response given to the interview items by respondents and observation of documents.

Syftet med vår studie är att beskriva några pedagogers syn på TAKK i förskolan samt att se hur och varför de väljer att arbeta med det, i de två förskolor som vi gjort studien på. Vi har också valt att undersöka vilka för- och nackdelar det eventuellt kan finnas med TAKK.Arbetet ger en översikt av tidigare forskning som handlar om TAKK, AAC, kommunikation och språkutveckling. Med hjälp av metoden kvalitativa intervjuer så har vi fått fram svar på följande frågeställning:•Hur och när arbetar pedagogerna i förskolan med TAKK?•Varför använder de TAKK i verksamheten?•Vilka fördelar respektive nackdelar finns det med att använda TAKK?Vi har valt att utgå från det sociokulturella perspektivet i vår studie.De som vi har intervjuat är alla positiva till TAKK, och de menar att det främjar barns språkutveckling. De anser också att man inte måste ha barn med särskilda behov på förskolan för att arbeta med TAKK, utan det är en positiv metod för alla barn. Slutsatsen som vi kommit fram till är att TAKK är något som alla barn har behov av för att göra sig hörda och förstådda. Trotts det så används det inte i så stor omfång fast pedagogerna har kunskap om det.

No description available.

The scientific community is undergoing a paradigm shift with the realization that the formation of carbonate minerals with diverse compositions and textures can be understood within the framework of multiple pathways to mineralization. A variety of common minerals can form via an amorphous pathway, where molecules or clusters aggregate to form a metastable amorphous phase that later transforms to one or more crystalline polymorphs. Amorphous calcium carbonate (ACC) is now recognized in a wide variety of natural environments. Recent studies indicate the chemical signatures and properties of the carbonate polymorphs that transform from an ACC pathway may obey a different set of dependencies than those established for the "classical" step-growth process. The Mg content of ACC and calcite is of particular interest as a minor element that is frequently found in ACC and the final crystalline products of calcified skeletons or sediments at significant concentrations. Previous studies of ACC have provided important insights into ACC properties, but a quantitative understanding of the controls on ACC composition and the effect of mineralization pathway on Mg signatures in calcite has not been established. This study utilized a new mixed-flow reactor (MFR) procedure to synthesize ACC from well-characterized solutions that maintain a constant supersaturation. The experimental design controlled the input solution Mg/Ca ratio, total carbonate concentration, and pH to produce ACC with systematic chemical compositions. Results show that ACC composition is regulated by the interplay of three factors at steady state conditions: 1) Mg/Ca ratio, 2) total carbonate concentration, and 3) solution pH. Findings from transformation experiments show a systematic and predictable chemical framework for understanding polymorph selection during ACC transformation. Furthermore, results suggest a chemical basis for a broad range of Mg contents in calcite, including high Mg calcite. We find that the final calcite produced from ACC is similar to the composition of the initial ACC phase, suggesting that calcite composition reflects local conditions of formation, regardless of the pathway to mineralization. The findings from this study provide a chemical road map to future studies on ACC composition, ACC transformation, polymorph selection, and impurities in calcite. / Ph. D.

<p>Genom att fusionera (sammanföra) data från olika sensorer kan ett resultat uppnås som ger mer än de enskilda sensorerna var för sig. Här utreds vilka sensorer och sensorfusionsmetoder som kan vara aktuella att använda för Scanias adaptiva farthållare (ACC). Den adaptiva farthållaren anpassar det egna fordonets hastighet inte bara till en förinställd hastighet utan även till framförvarande fordons hastighet. Scanias ACC-system använder idag en radar för måldetektering.</p><p>Det finns ett antal algoritmer och arkitekturer som passar för sensorfusionssystem beroende på nivån hos sensordatan och användningsområdet. Minstakvadratmetoder kan användas då data ska matchas mot en fysisk modell, ofta med lågnivådata. När tillgänglig data är på den nivån att den används direkt för att fatta beslut kan sannolikhetsmetoder användas. Intelligent fusion består av kognitiva modeller som avser härma den mänskliga beslutsprocessen. Till detta passar data på hög nivå.</p><p>Två lösningar, för två olika sensoruppsättningar, har tagits fram. Båda lösningarna är uppbyggda av bayesiska nätverk. Det första nätverket fusionerar data från den befintliga radarenheten med data från en kamera som detekterar vägmarkeringar. Resultaten visar att filbyten kan upptäckas tidigare i och med fusionen. Det andra nätverket använder sig av två radarenheter, den ursprungliga samt en likadan enhet till, vilket resulterar i ett bredare synfält. Nätverket avgör vilka mål hos respektive radar som kan anses vara samma matchade mål. Informationen kan användas för att öka redundansen i systemet samt för att upptäcka mål tidigare än förut.</p> / <p>By fusing data from different sensors a result can be achieved that is worth more than the data from each sensor by itself. Which sensors and sensor fusion methods that could be used in Scania's adaptive cruise control system (ACC) is investigated. The ACC system adapts the vehicle's speed not only to a driver decided set speed but also to the speed of preceding vehicles. Scania's ACC system uses a radar for target detection.</p><p>There exists a number of algorithms and architectures fit for use in sensor fusion systems. Which one to use depends on the level of the data to be fused and on the field of application. Least square methods are used when matching data to a physical model, data to be used is often at a low level. When working with data at decision level, probability methods are favored. Another example is intelligent fusion, cognitive methods intending to mimic the human decision process. Suitable data is data at a high level.</p><p>Two solutions, for two different sensor sets, are proposed. Both solutions are made out of Bayesian networks. The first one fuses data from the existing radar unit with data from a camera which detects lane markings. The results show that lane changes can be detected earlier thanks to the fusion. The second network uses two radar sensors of the same kind as the first, resulting in a wider field of view. The network decides which ones of each radars targets that are the same matching targets. This information could be used to increase the redundancy of the system and to detect targets earlier.</p>

This master´s thesis deals with an air cooled condenser. The specific attention is focused on the condenser in the Brno´s waste-to-energy plant SAKO. The general process of calculation of the heat transfer coefficient is introduced, which is the base for the calculation of the condenser´s output. This process is later used for the calculation of a specific condenser. A considerable part of the thesis is concentrated on the analysis of behavior of the condenser of SAKO in various conditions from the theoretical point of view and then also in terms of real operation using provided operational data.

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.