Do you need help determining appropriate measures and feasible data collection methods for program evaluations within integrated primary care? In this 3-hour preconference workshop, leaders from CFHA’s Research & Evaluation Committee and Families, Systems, & Health journal will provide practical training in conducting rigorous program evaluations. This workshop will help you identify appropriate measures to answer your key questions as well as data collection methods that balance quality and feasibility. This workshop is designed for those who are planning, conducting, or revising a program evaluation, as attendees will apply the material to their own personal projects within interactive small groups.

Sweden is currently going through changes in curricula, syllabuses and subject plans for elementary school and upper secondary school in order to adapt to the growing need of digital competence in the society. Inicio is an organisation that strives to help schools adjust to these changes in strategy. Inicio arranges events where students can work with educational user devices, designed to educate the user in specific areas. Inicio wants to understand how their users learn, while using the educational user devices. This report answers that question through the use of a learning framework that describes how usage data can be collected and analyzed. In addition, the framework allows analysis of both the devices and the events themselves. This gives Inicio the ability to measure the quality of what they provide and make improvements where necessary. The framework is built to be general enough to be applicable for future areas that Inicio may want to expand into. The finished framework is the result of an iterative process where applicability, scalability and ease of use have been the main focus. This report provides results in the form of the framework, two dream scenarios, an implementation example for a current device, documentation and a visual aid to simplify the use of the framework. The dream scenarios are made up use cases designed to test the framework for future products in both hardware and software environments. / Sverige går för närvarande genom förändringar i läroplaner, kursplaner och ämnesplaner för grundskolan och gymnasieskolan för att anpassa sig till det växande behovet av digital kompetens i samhället. Inicio är en organisation som strävar efter att hjälpa skolorna att anpassa sig till dessa förändringar i strategin. Inicio arrangerar events där eleverna kan arbeta med pedagogiska användaranordningar, utformade för att utbilda användaren på specifika områden. Inicio vill förstå hur användarna lär sig, medan de använder de pedagogiska användaranordningarna. Denna rapport svarar på den frågan genom att använda ett inlärningsramverk som beskriver hur användningsdata kan samlas in och analyseras. Dessutom möjliggör ramverket analys av både enheterna och eventen i sig. Detta ger Inicio möjligheten att mäta kvaliteten på vad de tillhandahåller och utföra förbättringar vid behov. Ramverket är byggt för att vara generellt nog för att kunna tillämpas på framtida områden som Inicio kan vilja expandera till. Det färdiga ramverket är resultatet av en iterativ process där användbarhet, skalbarhet och användarvänlighet har varit huvudfokus. Rapporten erbjuder resultat i form av ramverket, två drömscenarier, ett praktiskt exempel för en aktuell anordning, dokumentation och ett visuellt hjälpmedel för att förenkla användningen av ramverket. Drömscenarierna består av användarfall som är utformade för att testa ramverket för framtida produkter i både hårdvaruoch mjukvarumiljöer.

Energy utilization in Sweden has been on a rise since the 1980’s and the industrial sector has been its highest consumer. The construction industry plays a central role in building and developing cities for a population which is increasing rapidly year by year. Environmental awareness has given incentives to reduce carbon dioxide emissions and to make operations more sustainable. The construction industry faces three main challenges in regards to sustainability which are, material usage, vehicle fleets, and machine parks. Vehicles and machines are integral parts within the construction industry, however, how to reduce their environmental impact is a relatively new research area with many challenges. The conclusion that carbon dioxide emissions must be reduced is one that has been reached by the construction industry in Sweden. One way to study this aspect is by collecting and managing data on their fuel consumption since the vehicles and machines operate almost exclusively on fossil fuels. Data collection on fuel consumption by vehicles and machinery will give insight to what factors increase or decrease it. Analyzing these factors will allow for reductions to be made in terms ofcarbon dioxide emissions and costs. The aim of this report is therefore to investigate the aspect of data collection and management on fuel consumption in vehicles and machinery. The report is the result of work conducted in cooperation with the Nordic construction and development company NCC. NCC has set a goal for reducing climate impacts from direct operations by 50% between the years 2015 and 2020. In order for this to be achieved, carbon dioxide emissions resulting from fuel consumption have to be accounted for. As this is a new research area, this report is to serve as a baseline for NCC to get an overview of what challenges and possibilities there are with efficient data collection and management on fuel consumption. The study is initiated by analyzing the three main aspects which are taken into consideration within this study. The first aspect is authoritative requirements which are demands from authorities such as municipalities or the Swedish Transport Administration. The second is the contractors such as NCC which have to meet these requirements. The final aspect is the suppliers who contractors hire for projects. Furthermore, interviews are carried out to gain insight on experiences of persons within the field and the challenges they have faced. A study on Norrtälje Harbor, an old industrial harbor turning into a new city district, is also conducted as there is available data from the vehicles and machines in this project. Finally, a gap-analysis is constructed in order to gain an overview of NCC’s present standings, future goals, andlimitations in terms of data collection and management from vehicles and machinery. The findings of this report conclude that a lack of standard is the biggest challenge which theindustry is facing. Authorities face challenges on how to set standards while the lack of standardsleads to different methods of data collection from contractors and suppliers. It is possible tocollect data from vehicles and machines but calculations are currently based on patterns and donot give a true view of the fuel consumption. Factors, such as driving habits and environment can affect the fuel consumption, therefore the data collected should take all these factors into consideration. Benefits that a company may gain by having this data include increase incompetitiveness due to environmental awareness and transparency as well as also lower costsas less fuel will be purchased. Reducing fuel consumption will ultimately reduce carbon dioxideemissions, which is the industry’s and NCC overall goal. / Energianvändningen i Sverige har stigit sedan 1980-talet och industrisektorn har bidragit mest till detta. Byggbranschen står för utformningen av städer för en snabbt växande befolkning. Miljömedvetenhet har gett organisationer incitament att minska koldioxidutsläppen ochutveckla mer hållbara verksamheter. Materialanvändning, fordonsflottor och maskinparker utgör de tre största utmaningarna inom byggbranschens klimatarbete. Fordon och maskiner är grundläggande delar inom byggbranschens verksamhet, men minskningen av denna miljöpåverkan är ett relativt nytt forskningsområde med många utmaningar. Aktörerna inom byggbranschen har utvecklat klimatstrategier för att minska koldioxidutsläppen där man bland annat vill samla in data om bränsleförbrukningen hos fordon och maskiner. Fordon och maskiner drivs huvudsakligen med fossila bränslen och genom att kartlägga denna förbrukning kan koldioxidutsläppen minskas. Datainsamling om fordon och maskiners bränsleförbrukning ger förståelse gällande vilka faktorersom ökar eller minskar förbrukningen. Genom att analysera dessa faktorer är det möjligt att minska koldioxidutsläpp och kostnader. Syftet med denna rapport är därför att undersöka datainsamling och hantering angående bränsleförbrukning för fordon och maskiner. Rapporten är resultatet av ett arbete som bedrivits i samarbete med det Nordiska bygg- och utvecklingsbolaget NCC. NCC har satt upp ett mål för att minska klimatpåverkan fråndirektverksamheten med 50% mellan åren 2015 och 2020. För att detta ska kunna uppnås måstekoldioxidutsläpp från bränsleförbrukningen redovisas. Eftersom detta är ett nyttforskningsområde, är rapport en utgångspunkt för att NCC ska få en överblick över vilka utmaningar och möjligheter det finns med effektiv datainsamling och hantering avbränsleförbrukning. Studien initieras genom att analysera de tre huvudaspekter som måste beaktas inom detta ämnesområde. Första aspekten är kraven som ställs av myndigheter som kommuner och Trafikverket. Den andra aspekten är NCC entreprenörer som måste uppfylla dessa krav. Sista aspekten är leverantörerna som anställs av entreprenörerna inom projekt. Det övergripandesynsättet i studien är därför att analysera varje aspekt separat för en djupare förståelse för derasrespektive samband inom detta ämne. Vidare genomförs intervjuer för att få insikt omerfarenheter från personer inom studieområdet och de utmaningar de har mött. En studie av Norrtälje hamn, en gammal industrihamn som omvandlas till ett nytt stadsdelsområde,genomförs, eftersom det finns tillgängliga data från fordon och maskiner i detta projekt. Slutligen konstrueras en gapanalys för att få en överblick över NCC:s nuvarande läge, framtidamål och begränsningar när det gäller datainsamling och hantering från fordon och maskiner. Slutsatsen som dras är att brist på standard är den största utmaningen som industrin står inför. Myndigheterna står inför utmaningar om hur man kan ställa krav, medan bristen på dem leder till olika metoder för datainsamling från entreprenörer och leverantörer. Det går att samla in data från fordon och maskiner, men beräkningarna är för närvarande baserade på schabloner och ger inte en sann bild av bränsleförbrukningen. Faktorer som körvanor och miljö kan påverka bränsleförbrukningen, därför bör de insamlade uppgifterna ta hänsyn till alla dessa faktorer. Fördelarna med att ha dessa data tillgängliga är att det öka konkurrensen på grund avmiljömedvetenhet och öppenhet, samt minska kostnader för inköp av bränsle. Att minska bränsleförbrukningen kommer i slutändan att minska koldioxidutsläppen, vilket är branschens och NCC:s övergripande mål.

In past years many industries have utilized simulation as a means for decision making. That wave has introduced simulation as a powerful optimization and development tool in the manufacturing industry. Input data collection is a significant and complex event in the process of simulation. The simulation professionals have grown to accept it is as a strenuous but necessary task. Due to the nature of this task, data collection problems are numerous and vary depending on the situation. These problems may involve time consumption, lack of data, lack of structure, etc. This study concentrates on the challenges of input data collection for Discrete Event Simulation in the manufacturing industry and focuses particularly on speed, efficiency, data completeness and data accuracy. It has been observed that many companies have recently utilized commercial databases to store production data. This study proposes that the key to faster and more efficient input data collection is to extract data directly from these sources in a flexible and efficient way. An approach is introduced here to creating a custom software tool for a manufacturing setting that allows input data to be collected and formatted quickly and accurately. The methodology for the development of such a custom tool and its implementation, Part Data Collection, are laid out in this research. The Part Data Collection application was developed to assist in the simulation endeavors of Lockheed Martin Missiles and Fire Control in Orlando, Florida. It was implemented and tested as an aid in a large simulation project, which included modeling a new factory. This implementation resulted in 93% reduction in labor time associated with data collection and significantly improved data accuracy.

Automated data acquisition has revolutionized the reliability of product design in recent years. A noteworthy example is the improvement in the design of aircrafts through field data. This research proposes a similar improvement in the reliability of process design of earthmoving operations through automated field data acquisition. The segment of earthmoving operations addressed in this research constitutes the truck-loader operation. Therefore, the applicability of this research extends to other industries involving truck-operation such as mining, agriculture and forest logging and is closely related to wheel-based earthmoving operations such as scrapers. The context of this research is defined by data collection needed to increase the validity of the results obtained by analysis tools such as simulation, performance measures and graphical representation of variance in an activity's performance, and the relation between operating conditions and the variance in an activity's performance. The automated cycle time data collection is facilitated by instrumented trucks and the collection of information on operating conditions is facilitated by image database and paper forms. The cycle time data and the information on operating conditions are linked together to form the experience database. This research developed methods to extract, quantify and understand the variation in each component of the earthmoving cycle namely, load, haul and return, and dump activities. For the load activity, the simultaneous variation in payload and load time is illustrated through the development of a PLT (PayLoad Time) Map. Among the operating conditions, material type, load area floor, space constraints and shift are investigated. A dynamic normalization process of determining the ratio of actual travel time to expected travel time is developed for the haul and return activities. The length of the haul road, sequence of gear downshifts and shift are investigated for their effect on the travel time. The discussion on the dump activity is presented in a qualitative form due to the lack of data. Each component is integrated within the framework of the experience database. The implementation aspects with respect to developing and using the experience database are also described in detail. The practical relevance of this study is highlighted using an example. / Ph. D.

This study addressed the complex issue of data collection in program evaluation. The researcher sought to understand the influences affecting the quality and utility of data in program evaluation. The data collection process was examined through a single case study of a bilingual education program located in California. Information for this study was obtained through open-ended interviews with project staff, classroom teachers, and external evaluators. Other sources of information included records, documents, a computer database, and electronic mail correspondence with program officers. The researcher used Non-numerical Unstructured Indexing Searching and Theory Building (NUD*IST) computer software to manipulate interview transcriptions, records and documents. Emerging from the data were key categories and themes that were presented in narrative form. The researcher found that data collection was grounded in the context in which it occurs and was therefore, highly dependent on program staff. Data collection requires willing, qualified staff with an understanding of technology, assessment, and evaluation methodology.

That data is being collected surely, does not come as a surprise to users. Although, the question that should be asked today goes more in the lines of, do we know to what extent? Do we need to be aware? Is it bad, is it good? Big data collection is a worm hole of endless discussion and general complexity but is at the same time essential to understand to some degree. This study tries to examine how Meta, as one of the biggest companies today, pushes material in their newsflow in relation to how audiences perceive data collection as a phenomenon. Through theoretical foundation and previous research it is argued how negligence and unawareness can present itself unhealthy in the dynamic of how data is collected. This is illustrated through qualitative methods using thematic analysis by interviews and qualitative analysis of text. Results came to show that there is an interesting point to make in the data dynamic where negligence and unawareness might be a fact.

Wireless sensor networks (WSNs) typically consist of a significant number of inexpensive sensor nodes, each of which is powered by a battery or another finite energy source that is difficult to replace because of the environment they are in or the cost of doing so. The applications of WSNs include military surveillance, disaster management, target tracking and monitoring environmental conditions. In order to increase the lifespan of WSNs, energy-efficient sensing and communication approaches for sensor nodes are essential. Recently, there has been an increase in interest in using unmanned aerial vehicles (UAVs) as portable data collectors for ground sensor nodes in WSN. Several approaches to solving effective communication between sensor nodes and the fusion center have been investigated in this thesis. Because processing, sensing range, transmission bandwidth, and energy consumption are always limited, it is beneficial not to use all the information provided at each sensor node in order to prolong its life span and reduce communication costs. In order to address this problem, first, efficient measurement quantization techniques are proposed using a single fusion center and multiple sensors. The dynamic bit distribution is done among all the sensors and within the measurement elements. The problem is then expanded to include multiple fusion centers, and a novel algorithm is proposed to associate sensors to fusion centers. The bandwidth distribution for targets which are being monitored by several sensors is addressed. Additionally, how to use the situation in which the sensors are in the coverage radius of multiple fusion centers in order to share the targets between them is discussed. Finally, performance bounded data collection algorithms are proposed where the necessary accuracy for each target is specified. In order to determine the minimum number of data collectors needed and their initial placement, an algorithm is proposed. When there are fewer fixed data collectors than there are regions to collect the data from, a coverage path planning method is developed. Since the optimal solution requires an enormous computational requirement and not realistic for real-time online implementation, approximate algorithms are proposed for multi-objective integer optimization problems. In order to assess each suggested algorithm's effectiveness, many simulated scenarios are used together with baselines and simple existing methods. / Thesis / Doctor of Philosophy (PhD)

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