Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2017 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 74-79). / Scientific visualizations are central to the representation and communication of data in ways that are at once efficient and effective. Numerous data types have established unique formats of representation. In the context of three-dimensional (3D) data sets, such information is often presented as a 3D rendering, a video or an interactive application. The purpose of such visualization is often to emulate the physical, three-dimensional world; however, they remain inherently virtual. Recent advancements in additive manufacturing are making it possible to 'physicalize' three-dimensional data through 3D printing. Still, most 3D printing methods are geared towards single material printing workflows devoid of the ability to physically visualize volumetric data with high fidelity matching their virtual origin. As a result, information and detail are compromised. To overcome this limitation, I propose, design and evaluate a workflow to 'physicalize' such data through multi-material 3D printing. The thesis focuses on methods for voxel-based additive fabrication at high spatial resolution of three-dimensional data sets including - but not limited to point clouds, volumes, lines and graphs, and image stacks. This is achieved while maintaining the original data with high fidelity. I demonstrate that various data sets - often visualized through rasterization on screen - can be translated into physical, materially heterogeneous objects, by means of multi-material, voxel-based 3D printing. This workflow - its related tools, techniques and technologies contained herein - enables bridging the gap between digital information presentation and physical material composition. Developed methods are experimentally tested with various data across scales, disciplines and problem contexts - including application domains such as biomedicine, physics and archeology. / by Dominik Kolb. / S.M. / S.M. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2006. / Includes bibliographical references (p. 48-49). / Thesis statement: The purpose of this thesis is threefold: * Define the role and need of systems engineers/integrators within a large organization. * Analyze the system engineering procedures and availability of systems engineers/integrators to fill the need within multiple business units of a large multinational corporation and recommend best practices for development of system engineers/integrators. This thesis will investigate a product oriented company which operates in various market segments. This company, a manufacturer with a history of producing reliable and scalable products, places heavy emphasis on systems engineering. This, in turn, creates the need for highly experienced and efficient system engineers/integrators. / Thesis statement: The purpose of this thesis is threefold: * Define the role and need of systems engineers/integrators within a large organization. * Analyze the system engineering procedures and availability of systems engineers/integrators to fill the need within multiple business units of a large multinational corporation and recommend best practices for development of system engineers/integrators. This thesis will investigate a product oriented company which operates in various market segments. This company, a manufacturer with a history of producing reliable and scalable products, places heavy emphasis on systems engineering. This, in turn, creates the need for highly experienced and efficient system engineers/integrators. / by Rajeev Dubey. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2003. / Includes bibliographical references. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Despite its development and suitability to many specialties of medicine for the past forty years and the driving demands of an aging population, telemedicine has not made significant progress in deployment or commercialization. Why is this? Three case studies of health networks were used to identify the barriers to the widespread use of telemedicine in home healthcare and other applications of medicine. These barriers were further described and analyzed using the framework for disruptive technologies presented in Clayton Christensen' s The Innovator' s Dilemma. Although many studies assert that the slow adoption rate of telemedicine is explained by questions of efficacy and cost, this analysis proposes that the change in value networks posed by telemedicine technology is the greatest reason for its anemic implementation. Telemedicine changes the structure of the healthcare sector changing the organizational dynamics and values of the many players. The changes in structure are explored using the case studies and the successes and failures experienced by the health networks when implementing telemedicine across medical specialties. In order to harness this technology, recommendations are directed at organizations that need to evaluate new technologies differently and change their behavior with respect to competitors. Public policy needs to recognize the need for a greater thrust in long-term investments in telemedicine research, greater awareness of telemedicine in medical education and in taking the lead in developing standards, guidelines and protocols for telemedicine networks. Research also needs to be encouraged in newer clinical areas and existing standards and technologies in mature telemedicine application areas such as teleradiology and telepathology may be used in medical specialties where telemedicine is not yet a mainstream application. Moreover, the technology needs to become more 'human-centered' , to reduce technology barriers for both providers and patients amongst whom the elderly may be predominant. / by Shaheen Malik. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2006. / Includes bibliographical references (p. 140-144). / The RFID industry is going through a sea of change and at different levels within the industry. Forecasts have been done on different facets of the RFID/EPC industry like the market size or the possible financial returns. However, the forecasts to date are not based on a collective view on the evolving, dynamic and inter-relating nature of such technology covering Retailers, Suppliers and Industry experts on the same landscape. The EPC Peloton Forecasting and Strategic Planning Tool was developed out of a need to collaborate and form consensus around the events and milestones that are critical for the widespread adoption of EPC for the Fast Moving Consumer Goods ("FMCG") industry. Though developed around its need in the RFID space, this tool can be used for decision making around any emerging technology. We are at a critical juncture in the history of RFID where there is excitement among stakeholders and the technology's promise needs to be harnessed by providing the stakeholders with a clear idea of (a) where the technology's future lies and (b) how consensus on how to achieve such a future can be facilitated. / (cont.) The Peloton Approach deals with how to identify or develop a technology forecasting methodology that could capture inputs from all dimensions of the industry and lay down a range of possible future paths. To address the latter issue of collaboration, the Peloton aids in identifying the various stakeholders and their stages of adoption and provide a platform for people at a similar level of adoption to collaborate or enable those seeking information to be able to get into the bandwagon and adopt relevant strategies. / by Vineet Thuvara. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2001. / Includes bibliographical references (leaves 104-105). / by Sean M. Newell. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 97-103). / Microblogging services, most notably Twitter, have become popular avenues to voice opinions and be active participants of discourse on a wide range of topics. As a consequence, Twitter has become an important part of the political battleground that journalists and political analysts can harness to analyze and understand the narratives that organically form, spread and decline among the public in a political campaign. A challenge with social media is that important discussions around certain issues can be overpowered by majoritarian or controversial topics that provoke strong reactions and attract large audiences. In this thesis we develop a method to identify the specific ideas and sentiments that represent the overall conversation surrounding a topic or event as reflected in collections of tweets. We have developed this method in the context of the 2016 US presidential elections. We present and evaluate a large scale data analytics framework, based on recent advances in deep neural networks, for identifying and analyzing election- related conversation on Twitter on a continuous, longitudinal basis in order to identify representative tweets across prominent election issues. The framework consists of two main components, (1) a dynamic topic model that identifies all tweets related to election issues using knowledge from news stories and continuous learning of Twitter's evolving vocabulary, (2) a semantic model of tweets called Tweet2vec that generates general purpose tweet embeddings used for identifying representative tweets by robust semantic clustering. The topic model performed with an average F-1 score of 0.90 across 22 different election topics on a manually annotated dataset. Tweet2Vec outperformed state-of-the- art algorithms on widely used semantic relatedness and sentiment classification evaluation tasks. To demonstrate the value of the framework, we analyzed tweets leading up to a primary debate and contrasted the automatically identified representative tweets with those that were actually used in the debate. The system was able to identify tweets that represented more semantically diverse conversations around each of the major election issues, in comparison to those that were presented during the debate. This framework may have a broad range of applications, from enabling exemplar-based methods for understanding the gist of large collections of tweets, extensible perhaps to other forms of short text documents, to providing an input for new forms of data-grounded journalism and debate. / by Prashanth Vijayaraghavan. / S.M.

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 70-73). / Ongoing humanitarian operations can suffer from the lack of medical item availability. The central problem thus becomes how to ensure the right item in the right place at the right time while maintaining appropriate costs. By means of a case study, this research grouped items by various item characteristics and assigned each group a common operating policy. The results of such item segmentation, and the application of common operating policies, was a theoretical increase over the current rule of thumb, single operating policy by 22% in average expected item availability and a decrease in total costs of 2-8%. Yet, similar results were achieved without segmentation. The major conclusion is that consideration of demand variability as a means to achieve greater item availability is key. The determination of appropriate costs becomes a transparent one for the decision-maker. More generally, this approach facilitates the comparison of various inventory management scenarios and the assumption of informed levels of risk. / by Brent Turner. / M. Eng. in Supply Chain Management

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 61-69). / The miracle of life is only possible thanks to a wide range of biochemical interactions between assortments of molecular agents. Amidst these agents, which enable all cellular activities, proteins are undoubtedly among the most important groups. Proteins facilitate countless intra- and inter-cellular functions, from regulation of gene expression to immune responses to muscle contraction, but they rarely act in isolation. These are the interactions between proteins, known as protein-protein interactions or PPIs, which sustain the fundamental role of proteins in all living organisms. PPIs are also central to the study of diseases and development of therapeutics. Aberrant human PPIs are the primary cause of many life-threatening conditions, such as Alzheimer, Creutzfeldt-Jakob, and cancer; making the regulation of PPI activities a promising direction for pharmaceutical development. Despite the indisputable importance of PPIs, so far only a tiny fraction of all human PPIs has been discovered, and our current understanding of the core mechanisms and primary functionalities is insufficient. While computational methods in general and machine learning in particular showed encouraging potential to address this challenge, their application in real-life has been limited. To mitigate this gap and make sure computational results perform as well in real-life, we introduce a set of gold-standard machine learning practices called NetPPI. The contributions of this thesis include NetPPI, a minimally-biased, carefully curated dataset of experimentally detected PPIs for training and evaluation of machine learning models; a comprehensive study of protein sequence representations for use with discriminative models; and data splitting methodology for machine learning purposes. We also present the Bilinear PPI model for state-of-the-art PPI prediction. Finally, we propose fundamental biological insight on the nature of PPIs, based on performance analysis of different prediction models. / by Kfir Schreiber. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2001. / Includes bibliographical references (leaves 68-69). / An overview of the operation of a modem, high bypass ratio, dual spool turbofan engine is presented to identify the multitude of system level interactions that must be considered when developing such an engine. The Design Structure Matrix (DSM) is used to demonstrate how it maps these relationships and, if utilized in the right manner, can reduce the occurrence of escapes (i.e., a deliverable that does not meet customers' expectations). The context of this thesis is the complex system design, and development process, of a commercial aircraft gas turbine engine (specifically the Pratt & Whitney PW4000 engine family). Unlike previous gas turbine engine DSM work, the matrix created in this thesis is generated from the point of view of the Systems Engineering organizations at Pratt & Whitney. The sequenced matrix captures the non-local knowledge that is currently absent from Pratt & Whitney's existing knowledge management documentation. Testing the DSM against past instances of rework and unexpected design issues substantiates its validity as the basis for performing this function. Finally, examples are presented to demonstrate how the DSM can be used to prevent future escapes. / by Glenn D. Bartkowski. / S.M.

Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, System Design and Management Program, 2009. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 82-83). / Telecommunication technology has had a profound impact on our daily lives. It has enabled organizations to be more competitive by reducing the need for physical proximity and fostering collaboration. In recent years especially, data networks have been especially prominent, with the obvious example being the Internet. Work that was once conducted by phone and fax is now increasingly being done by VolP, e-mail and IM. For years telecommunication companies had focused in making available communication between person-to-person as well as multi-person and mobile communication, but none had focused on the content of the voice communication. This thesis presents a functioning product to address the needs of such users by applying a systems thinking approach to visualize and manage complexity through the whole process from the product idea generation to the business model. A detailed assessment of the users' needs and description of the product's user-centric design is provided. User experience design principles and legal constraints were considered throughout the development process. We propose to add value and differentiate the product by providing users with options to manage the content of their calls. At the most basic level, we give free audio-to-text transcripts with built-in features that could users save time and be more productive. nexiwave was built using principles promulgated in the System Design and Management Program classes. / by Cynthia Munoz Jugo [and] Benjamin Jiang. / S.M.in Engineering and Management