One vital task of a project's owner is to determine a reliable and reasonable construction time for the project. A U.S. highway agency typically uses the bar chart or critical path method for estimating project duration, which requires the determination of construction logic. The current practice of activity sequencing is challenging, time-consuming, and heavily dependent upon the agency schedulers' knowledge and experience. Several agencies have developed templates of repetitive projects based on expert inputs to save time and support schedulers in sequencing a new project. However, these templates are deterministic, dependent on expert judgments, and get outdated quickly. This study aims to enhance the current practice by proposing a data-driven approach that leverages the readily available daily work report data of past projects to develop a knowledge base of construction sequence patterns. With a novel application of sequential pattern mining, the proposed framework allows for the determination of common sequential patterns among work items and proposed domain measures such as the confidence level of applying a pattern for future projects under different project conditions. The framework also allows for the extraction of only relevant sequential patterns for future construction time estimation.

Cost overrun is prevalent in the construction industry. Usually, an owner sets a budget at the preliminary phase of a project which changes over time. Past studies are focused on analyzing the cost growth of design-bid-build projects during construction. Limited efforts have been made to analyze details of projects delivered with the Construction Manager General Contractor (CM/GC) method. This study tracks and analyzes the construction cost variation of a project from the conceptual phase to the design completion phase. The analysis is presented with a case study of a new stadium construction project. It identifies that the changes in the scope and design of the project due to the change in available budget were a major reason for variation in the cost estimates over time. Further, this study identifies a) trades with the highest variation in subcontractors’ bids, b) trades that were most overestimated, and c) trades that were most underestimated. The findings of this study is expected to aid owners, designers, and contractors of future projects in improving the preparation, planning, and estimating of future projects; reducing cost variation within trades; and optimizing the amount of contingency required to ensure the successful completion of similar projects.

No description available.

In today’s architecture, engineering, and construction (AEC) industry, building information modeling (BIM) technologies and practices are making a significant difference in how building projects are delivered. BIM models and tools let stakeholders visualize, simulate, and analyze how a building might behave, perform, or appear—with more precision than ever before. BIM technology and practices are not only improving design and construction processes by delivering projects faster, more cost effectively, and more sustainably, but are also helping BIM professionals by expanding career possibilities within the field. This paper identifies key personnel in AEC industry who are taking advantage of BIM technologies and practices and explains how BIM has enhanced their career paths. The study found that new processes of BIM enhance the careers of existing professionals and create new career paths for young professionals. Until recently, positions like BIM engineer/BIM manager did not exist, but now they are key positions in many companies. BIM is also opening up positions for young engineers in nontraditional industries like manufacturing, energy, media and entertainment, healthcare companies, and facility management.

Percent within limits (PWL) is a commonly used quality control/quality assurance measure of highway pavement materials and construction, and it is a popular index for adjusting pay factors. However, PWL is based on the assumption of normal distribution of quality characteristics (e.g., concrete compressive strength and asphalt air voids). Skewness and kurtosis, which are common forms of statistical nonnormal distributions, can potentially bias the acceptance pay factor calculations. To examine this potential pay bias, simulations were performed to investigate the magnitude and the direction (overestimation or underestimation) of pay factor calculations. The study revealed that for both one-sided and two-sided specification limits, bias in pay factors not only did vary in magnitude but also reversed in direction over various ranges of PWL. These analyses showed that for a one-sided upper specification limit, on average, a positive skewness and kurtosis can underestimate the pay factor of an acceptable quality level population by 0.90%, and overestimates a rejectable quality level population by 3.8%. This leads to falsely penalizing acceptable products and rewarding bad products. The same was true for two-sided limits, which again varied based upon the percent of defective materials at the tails of the distribution. This is a very important issue because these biases in pay factors can easily upset the relative profit margins of the contractor. Furthermore, this may not be easily detectable without a detailed and sophisticated analysis as outlined in this paper. For multiple quality characteristics based pay factors, analyses showed that the combined magnitude of these biases was not linearly cumulative. Findings of the study indicate that bias in pay was higher for lots with fewer sublots and higher skewness and kurtosis.

Le travail présenté dans ce mémoire s'inscrit dans le domaine des Environnements Informatiques pour l'Apprentissage Humain (EIAH), plus précisément celui de l'ingénierie des EIAH dans le cadre d'une approche de type « Learning Design ». Cette approche propose de construire des EIAH à partir de la description formelle d'une activité d'apprentissage. Elle suppose l'existence d'un langage de modélisation communément appelé EML (Educational Modelling Language) et d'un moteur capable d'interpréter ce langage. LDL est le langage sur lequel nous avons travaillé, en relation avec l'infrastructure LDI intégrant un moteur d'interprétation de LDL. L'EML est utilisé pour produire un scénario, modèle formel d'une activité d'apprentissage. L'EIAH servant de support au déroulement de l'activité décrite dans le scénario est alors construit de manière semi-automatique au sein de l'infrastructure associée au langage selon le processus suivant : le scénario est créé lors d'une phase de conception ; il est instancié et déployé sur une plate-forme de services lors d'une phase d'opérationnalisation (choix des participants à l'activité, affectation des rôles, choix des ressources et services) ; le scénario instancié et déployé est pris en charge par le moteur qui va l'interpréter pour en assurer l'exécution. Dans ce cadre, l'activité se déroule conformément à ce qui a été spécifié dans le scénario. Or il est impossible de prévoir par avance tout ce qui peut se produire dans une activité, les activités étant par nature imprévisibles. Des situations non prévues peuvent survenir et conduire à des perturbations dans l'activité, voire à des blocages. Il devient alors primordial de fournir les moyens de débloquer la situation. L'enseignant peut par ailleurs vouloir exploiter une situation ou une opportunité en modifiant l'activité en cours d'exécution. C'est le problème qui est traité dans cette thèse : il s'agit de fournir les moyens d'adapter une activité « à la volée », c'est-à-dire pendant son exécution, de manière à pouvoir gérer une situation non prévue et poursuivre l'activité. La proposition que nous formulons s'appuie sur la différentiation entre les données convoquées dans chacune des trois phases du processus de construction de l'EIAH : la conception, l'opérationnalisation et l'exécution. Nous exhibons un modèle pour chacune de ces phases, qui organise ces données et les positionne les unes par rapport aux autres. Adapter une activité « à la volée » revient alors à modifier ces modèles en fonction des situations à traiter. Certaines nécessitent la modification d'un seul de ses modèles, d'autres conduisent à propager les modifications d'un modèle vers un autre. Nous considérons l'adaptation « à la volée » comme une activité à part entière menée, en parallèle de l'activité d'apprentissage, par un superviseur humain qui dispose d'un environnement adéquat pour observer l'activité, détecter les éventuels problèmes et y remédier par intervention dans l'activité d'apprentissage en modifiant les modèles qui la spécifient. Pour développer les outils support à la modification et les intégrer dans l'infrastructure LDI, nous avons eu recours à des techniques de l'Ingénierie Dirigée par les Modèles. Les modèles manipulés dans ces outils en sont ainsi des données à part entière : les outils réalisés n'en offrent ainsi que plus de flexibilité et d'abstraction. Les modèles sont alors exploités comme des leviers pour atteindre et modifier les données ciblées par l'adaptation. / The work presented in this paper is in the field of Technology for Human Learning (TEL), specifically that of engineering in the context of TEL-type approach "Learning Design". This approach proposes to build ILE from the formal description of a learning activity. It assumes the existence of a common modeling language called EML (Educational Modelling Language) and an engine capable of interpreting this language. LDL is the language on which we worked in conjunction with the LDI infrastructure including a motor interpretation of LDL. The EML is used to produce a scenario, a formal model of learning activity. The ILE serving to support the conduct of the activity described in the scenario is then constructed semi-automatically in the infrastructure associated with the language using the following process: the script is created during a design phase; it is instantiated and deployed on a platform of services in an operational phase (selection of participants in the activity, role assignment, choice of resources and services); instantiated and deployed scenario is supported by the engine will interpret it to ensure its implementation. In this context, the activity takes place in accordance with what was specified in the script. It is impossible to predict in advance all that can occur in an activity, the activities are by nature unpredictable. Unforeseen situations can occur and lead to disturbances in the activity, or even blocks. It then becomes important to provide the means to break the deadlock. The teacher may also want to exploit a situation or opportunity by altering the activity in progress. This is the problem that is addressed in this thesis: to provide the means to adapt an activity "on the fly", that is to say while running, so you can not handle a situation provided and continue the activity. The proposal we make is based on the differentiation between data convened in each of the three phases of construction of the ILE: design, operationalization and implementation. We exhibit a model for each phase, which organizes the data and positions to each other. Adapt an activity "on the fly" then returns to modify these models in different situations to deal with. Some require the modification of one of its models, while others lead to propagate changes from one model to another. We consider adaptation "on the fly" as a separate activity conducted in parallel with the learning activity by a human supervisor has an adequate environment to observe the activity, identify potential problems and be remedied by intervention in the learning activity by modifying the templates that specify. To develop tools to support the change and integrate them into the LDI infrastructure, we have used the techniques of Model Driven Engineering. Handled in these models are tools and data in its own right tools and made no offer more flexibility and abstraction. The models are then used as levers to achieve and change the data targeted by the adaptation.

This masters thesis deals with renovations expensive spare parts for the use of special engineering technologies. The aim was to compare and evaluate the technical and economical technological processes used components renovations. In the theoretical part are written information obtained from literature sources dealing with the basic concepts, definitions and describes the most commonly used technology renovation. In their study were selected components for renovation, where it is necessary to use special methods of engineering technologies. The first part was chosen balancer shaft used for four-cylinder diesel engine Volkswagen. For component was suggested special technological process of repair, so as to achieve low prices, but also guarantee a high quality repair and threaten further damage. Price repairs were compared against the cost of a new spare part. Another component was selected renovation speed bump for truck Scania. For component was suggested technological process of repair. Prices renovations by various techniques were compared.

Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2016-10-17T18:29:55Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) phd_efsb_FINAL_BIBLIOTECA.pdf: 7882904 bytes, checksum: df094c44eb4ce5be12596263047790ed (MD5) / Made available in DSpace on 2016-10-17T18:29:55Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) phd_efsb_FINAL_BIBLIOTECA.pdf: 7882904 bytes, checksum: df094c44eb4ce5be12596263047790ed (MD5) Previous issue date: 2016-08-29 / FACEPE / Context: In Software Engineering, technology transfer has been treated as a problem that concernsonly two agents (innovation and adoption agents) working together to fill the knowledge gap between them. In this scenario, the transfer is carried out in a “peer-to-peer” fashion, not changing the reality of individuals and organizations around them. This approach works well when one is just seeking the adoption of a technology by a“specific client”. However, it can not solve a common problem that is the adoption of new technologies by a large mass of potential new users. In a wider context like this, it no longer makes sense to focus on “peer-to-peer” transfer. A new way of looking at the problem is necessary. It makes more sense to approach it as diffusion of innovations, where there is an information spreading in a community, similar to that observed in epidemics. Objective: This thesis proposes a paradigm shift to show the adoption of programming languages can be formally addressed as an epidemic. This focus shift allows the dynamics of programming language adoption to be mathematically modelled as such, and besides finding models that explain the community’s behaviour when adopting programming languages, it allows some predictions to be made, helping both individuals who wish to adopt a new language that might seem to be a new industry standard, and language designers to understand in real time the adoption of a particular language by a community. Method: After a proof of concept with data from Sourceforge (2000 to 2009), data from GitHub (2009 to January 2016), a well-known open source software repository, and Stack Overflow (2008 to March 2016), a popular Q&A system for software developers, were obtained and preprocessed. Using cumulative biological growth functions, often used in epidemiological contexts, we obtained adjusted models to the data. Once with the adjusted models, we evaluated their predictive capabilities through repeated applications of hypothesis testing and statistical calculations in different versions of the models obtained after adjusting the functions to samples of different time frames from the repositories. Results: We show that programming language adoption can be formally considered an epidemiological phenomenon by adjusting a well-known mathematical function used to describe such phenomena. We also show that, using the models found, it is possible to forecast programming languages adoption. We also show that it is possible to have similar insights by observing user data, as well as data from the community itself, not using software developers as susceptible individuals. Limitations: The forecast of the adoption outcome (asymptote) needs to be taken with care because it varies depending on the sample size, which also influences the quality of forecasts in general. Unfortunately, we not always have control over the sample size, because it depends on the population under analysis. The forecast of programming language adoption is only valid for the analysed population; generalizations should be made with caution. Conclusion: Addressing programming languages adoption as an epidemiological phenomenon allows us to perform analyses not possible otherwise. We can have an overview of a population in real time regarding the use of a programming language, which allows us, as innovation agents, to adjust our technology if it is not achieving the desired “penetration”; as adoption agents, we may decide, ahead of our competitors, to adopt a seemingly promising technology that may ultimately become a standard. / Contexto: Em Engenharia de Software, transferência de tecnologia tem sido tratada como um problema pontual, um processo que diz respeito a dois agentes (os agentes de inovação e adoção) trabalhando juntos para preencher uma lacuna no conhecimento entre estes dois. Neste cenário, a transferência é realizada “ponto a ponto”, envolvendo e tendo efeito apenas nos indivíduos que participam do processo. Esta abordagem funciona bem quando se está buscando apenas a adoção da tecnologia por um “cliente” específico. No entanto, ela não consegue resolver um problema bastante comum que é a adoção de novas tecnologias por uma grande massa de potenciais novos usuários. Neste contexto mais amplo, não faz mais sentido focar em transferência ponto a ponto, faz-se necessária uma nova maneira de olhar para o problema. É mais interessante abordá-lo como difusão de inovações, onde existe um espalhamento da informação em uma comunidade, de maneira semelhante ao que se observa em epidemias. Objetivo: Esta tese de doutorado mostra que a adoção de linguagens de programação pode ser tratada formalmente como uma epidemia. Esta mudança conceitual na maneira de olhar para o fenômeno permite que a dinâmica da adoção de linguagens de programação seja modelada matematicamente como tal, e além de encontrar modelos que expliquem o comportamento da comunidade quando da adoção de uma linguagem de programação, permite que algumas previsões sejam realizadas, ajudando tanto indivíduos que desejem adotar uma nova linguagem que parece se apresentar como um novo padrão industrial, quanto ajudando projetistas de linguagens a entender em tempo real a adoção de uma determinada linguagem pela comunidade. Método: Após uma prova de conceito com dados do Sourceforge (2000 a 2009), dados do GitHub (2009 a janeiro de 2016) um repositório de projetos software de código aberto, e Stack Overflow (2008 a março de 2016) um popular sistema de perguntas e respostas para desenvolvedores de software, from obtidos e pré processados. Utilizando uma função de crescimento biológico cumulativo, frequentemente usada em contextos epidemiológicos, obtivemos modelos ajustados aos dados. Uma vez com os modelos ajustados, realizamos avaliações de sua precisão. Avaliamos suas capacidades de previsão através de repetidas aplicações de testes de hipóteses e cálculos de estatísticas em diferentes versões dos modelos, obtidas após ajustes das funções a amostras de diferentes tamanhos dos dados obtidos. Resultados: Mostramos que a adoção de linguagens de programação pode ser considerada formalmente um fenômeno epidemiológico através do ajuste de uma função matemática reconhecidamente útil para descrever tais fenômenos. Mostramos também que é possível, utilizando os modelos encontrados, realizar previsões da adoção de linguagens de programação em uma determinada comunidade. Ainda, mostramos que é possível obter conclusões semelhantes observando dados de usuários e dados da comunidade apenas, não usando desenvolvedores de software como indivíduos suscetíveis. Limitações: A previsão do limite superior da adoção (assíntota) não é confiável, variando muito dependendo do tamanho da amostra, que também influencia na qualidade das previsões em geral. Infelizmente, nem sempre teremos controle sob o tamanho da amostra, pois ela depende da população em análise. A adoção da linguagem de programação só é válida para a população em análise; generalizações devem ser realizadas com cautela. Conclusão: Abordar o fenômeno de adoção de linguagens de programação como um fenômeno epidemiológico nos permite realizar análises que não são possíveis de outro modo. Podemos ter uma visão geral de uma população em tempo real no que diz respeito ao uso de uma linguagem de programação, o que nos permite, com agentes de inovação, ajustar a tecnologia caso ela não esteja alcançando o alcance desejado; como agentes de adoção, podemos decidir por adotar uma tecnologia aparentemente promissora que pode vir a se tornar um padrão.

A highway construction cost index (HCCI) is an indicator of the purchasing power of a highway agency. Thus, it must reflect the actual construction market conditions. However, current methods used by most state departments of transportation are not robust enough to meet this primary goal due to (1) a significantly insufficient sample size of bid items used in HCCI calculation; and (2) inability to address the need to track highway construction market conditions in specific submarket segments such as, but not limited to, various project types, sizes, and locations. This study proposes an advanced methodology to overcome these apparent limitations using two new concepts: (1) dynamic item basket; and (2) multidimensional HCCIs. The dynamic item basket process identifies and utilizes an optimum amount of bid-item data to calculate HCCIs in order to minimize the potential error due to a small sample size, which leads to a better reflection of the current market conditions. Multidimensional HCCIs dissect the state highway construction market into distinctively smaller sectors of interest and thus, allow state Departments of Transportation to understand the market conditions with much higher granularity. A framework is developed to integrate these two concepts and a standalone prototype system, named the Dyna-Mu-HCCI System, is developed to automate the data-processing part of the framework. The historical bid data of the Montana Department of Transportation are used to evaluate the performance of the Dyna-Mu-HCCI System and measure the effects of the dynamic item basket (DIB) and multidimensional HCCIs. The results show an eightfold increase in terms of the number of bid items used in calculating HCCIs and at least a 20% increase in terms of the total cost of bid items used. In addition, the multidimensional HCCIs reveal different cost-change patterns from different highway sectors. For example, the bridge construction market historically shows a very different trend compared with the overall highway construction market. The new methodology is expected to aid state Departments of Transportation in making more-reliable decisions in preparing business plans and budgets with more accurate and detailed information about the construction market conditions. Further, the prototype Dyna-Mu-HCCI System is expected to significantly facilitate the HCCI calculation process and rapidly implement this new system.

In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with severities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.