No / The boundaries between different kinds of media spaces are complex and challenging. The convergence of computing, media, and telecommunications produces environments that contain elements of their origins, but also contain new components that allow interaction in new ways by new users with new kinds of information. This poses problems for effective human computer interaction and human media interaction because the paradigms are not well understood. Converged environments are driving these new uses just as the first PCs supported keyboards and then WIMP interfaces. Traditional models of human computer interaction are not adequate to deal with this complexity, and the shifting of the boundaries brought about by convergence.

Spanning 14 states in the northeast United States, the Appalachian Trail (AT) is a popular destination for outdoor recreation, with thousands of individuals attempting to thru-hike the AT every year. For its scenic views and accessibility from the cities, the AT is experiencing a record number of visitors raising concerns about the sustainability of the trail. Many trail organizations manage the AT to reduce the visitor impact on the outdoors. In this research, I study the role of information and communication technologies in promoting collaboration between these trail agencies and visitors. I identify the need for a formal communication channel between the stakeholders by examining the existing information-sharing practices of hikers and trail managers through social media analysis, interviews, and a design workshop. I present the design of an online discussion platform, the SmarTrail board, and conduct a field usability study with two AT trail clubs to evaluate the platform. Findings from the study reveal that centralized direct communication and streamlined information can support trail management on the AT by promoting collaboration within the trail community. The research paves the path for future research into the design of ICTs for driving nature conservation goals. / Master of Science / The Appalachian Trail (AT) in the northeast of the United States spreads across 14 states. It is accessible from many regional urban centers, offering recreational opportunities to thousands of individuals every year. It is also a popular site for thru-hiking, an endeavor to hike the trail from end to end in a year. Such popularity and accessibility to the trail put pressure on the natural resources, raising concerns about the sustainability of the trail. Management of the trail deals with minimizing the resource impact while preserving the trail experiences of the visitors. Thirty trail clubs maintain separate sections of the AT, and a number of trail organizations work together to manage the trail. The core of this management relies on the collaboration of these trail agencies with each other and the visitors. As communication is central to collaborations in everyday life and for the trail, I explore the practices and possibilities for information sharing and communication on the AT. Digital conservation refers to the technological developments that support and forward nature conservation goals. As the pristine environment of the trails and the AT are not barred from the reach of digital technology, the prevalence of smartphones among visitors presents opportunities for information and communication technologies (ICTs) to support the digital conservation of the trail. In this research, I study digital technology use among hikers and trail managers on the AT, particularly for information sharing. By analyzing comments on Reddit, conducting interviews with the AT trail managers, and organizing a workshop with long-distance hikers, I highlight the need for direct communication between these stakeholders. I present the design of an online discussion board called the SmarTrail platform as a formal communication channel between hikers and trail managers and evaluate it with two trail clubs on the AT. The results from the evaluation offer several use cases of mediated communication, highlighting its need and potential in supporting trail management on the AT. Centralized and formal communication can lead to effective trail management by engaging visitors in trail management, improving volunteer management for the clubs, and enabling knowledge sharing and coordination between the trail agencies. With design considerations for improving human-nature interaction and simplifying the available information for visitors and trail management authorities, this study informs the design of ICTs for trail environments that would forward the digital conservation goals on the AT.

No

Aligning Word2vec word embeddings using a compass in a system of Compass-aligned Distributional Embeddings (CADE) creates stable and accurate temporal word embeddings. This thesis seeks to expand the CADE framework into the area of dynamic topic modeling (DTM), where temporal word2vec embeddings can be used to describe temporally and unsupervised evolving topics. It also seeks to improve upon the CADE framework through a theoretical and experimental exploration of compass parameters, cluster and topic generation techniques, and topic descriptor creation. This method of Temporal Topic Embeddings with a Compass (TTEC) will be compared to other DTM techniques in the ability to create coherent and diverse clusters and will be shown to be competitive compared to traditional and transformer-aided DTM architectures. In addition to a qualitative discussion of results, there will be a political theoretical overview of the nature of this technique and potential use cases, with interviews from political actors of various backgrounds as to how the technique and machine learning as a whole can be used in the organizational setting. / Master of Science / Diachronic word embeddings look at how the context words appear in evolve over time. Dynamic Topic Modeling (DTM) is the ability to computationally discover topics and how they evolve over time. This thesis creates a DTM technique called Temporal Topic Embeddings with a Compass (TTEC) based off diachronic word embeddings, allowing a user to simultaneously look at word and topic evolution over time. There is also an exploration of the use case of TTEC and similar machine learning models within various political organizational settings through interviews.

With the dramatic increase and continued growth of digital information, developing Visual Analytic systems that support human cognition and insight generation are more necessary than ever before, but there is currently no content-agnostic method for measuring or com- paring how well a system facilitates analysis. Researchers in industry and academia are developing advanced tools that offer automated data analysis combined with support for human sense-making; tools for a wide variety of sense-making tasks are freely available. Now, the pressing question is: which tool works best, and for what? We show that using Shannon's entropy and self-information measures will provide a measure of the complexity reduction that results from an analyst's actions while sorting the information. Further, we demonstrate that reduced complexity can be linked to the knowledge gained. This is important, because a metric for objectively evaluating the success of current systems in generating insights would establish a standard that future tools could build on. This work could help guide researchers and developers in making the next generation of analytic tools, and in the age of big data the effect of such tools could potentially impact everyone. / Master of Science / With the dramatic increase and continued growth of digital information, developing systems that enables humans to make sense of all the data are more necessary than ever before, but there is currently no one-size-fits-all method for measuring or comparing how well a system helps people gain such insight. Rather than trying to pin down a definition of what insight is, we instead look at complexity reduction—with the intuition that, before we can make sense of complex data, we must somehow simplify it in a meaningful way. We show that using Shannon’s entropy and self-information values will provide a measure of the complexity reduction that results from an analyst’s actions while sorting information, and further demonstrate that reduced complexity can be linked to the knowledge gained. This work is important, because a metric for objectively evaluating the success of current systems in generating insights would establish a standard that future tools could build on. This work could help guide researchers and developers in making the next generation of analytic tools, and in the age of big data the effect of such tools could potentially impact everyone.

A recuperação de imagens baseada em conteúdo, amplamente conhecida como CBIR (do inglês Content-Based Image Retrieval), é um ramo da área da computação que vem crescendo muito nos últimos anos e vem contribuindo com novos desafios. Sistemas que utilizam tais técnicas propiciam o armazenamento e manipulação de grandes volumes de dados e imagens e processam operações de consultas de imagens a partir de características visuais extraídas automaticamente por meio de métodos computacionais. Esses sistemas devem prover uma interface de usuário visando uma interação fácil, natural e atraente entre o usuário e o sistema, permitindo que o usuário possa realizar suas tarefas com segurança, de modo eficiente, eficaz e com satisfação. Desse modo, o design da interface firma-se como um elemento fundamental para o sucesso de sistemas CBIR. Contudo, dentro desse contexto, a interface do usuário ainda é um elemento constituído de pouca pesquisa e desenvolvimento. Um dos obstáculos para eficácia de design desses sistemas consiste da necessidade em prover aos usuários uma interface de alta qualidade para permitir que o usuário possa consultar imagens similares a uma dada imagem de referência e visualizar os resultados. Para atingir esse objetivo, este trabalho visa analisar a interação do usuário em sistemas de recuperação de imagens por conteúdo e avaliar sua funcionalidade e usabilidade, aplicando técnicas de interação humano-computador que apresentam bons resultados em relação à performance de sistemas com grande complexidade, baseado em um estudo de caso aplicado à medicina / The content-based image retrieval (CBIR) is a challenging area of the computer science that has been growing in a very fast pace in the last years. CBIR systems employ techniques for extracting features from the images, composing the features vectores, and store them together with the images in data bases management system, allowing indexing and querying. CBIR systems deal with large volumes of images. Therefore, the feature vectors are extracted by automatic methods. These systems allow to query the images by content, processing similarity queries, which inherently demands user interaction. Consequently, CBIR systems must pay attention to the user interface, aiming at providing friendly, intuitive and attractive interaction, leading the user to do the tasks efficiently, getting the desired results, feeling safe and fulfilled. From the points highlighted beforehand, we can state that the human-computer interaction (HCI) is a key element of a CBIR system. However, there is still little research on HCI for CBIR systems. One of the requirements of HCI for CBIR is to provide a high quality interface to allow the user to search for similar images to a given query image, and to display the results properly, allowing further interaction. The present dissertation aims at analyzing the user interaction in CBIR systems specially suited to medical applications, evaluating their usability by applying HCI techniques. To do so, a case study was employed, and the results presented

L'auteur n'a pas fourni de résumé en français. / Integrated circuits evolution is driven by the trend of increasing operating frequencies and downscaling of the device size, while embedding more and more complex functionalities in a single chip. However, the continuation of the device-scaling race generates a number of technology challenges. For instance, the downscaling of transistor channel lengths induce short-channel effects (drain-induced barrier lowering and punch-through phenomena); high electric field in the devices tend to increase Hot electron effect (or Hot Carrier) and Oxide Dielectric Breakdown; higher temperatures in IC products generates an increase of the Negative Bias Temperature Instability (NBTI) effect on pMOS devices. Today, it is considered that the above reliability mechanisms are ones of the main causes of circuit degradation performance in the field. This dissertation will address the Hot Carrier (HC) and NBTI impacts on CMOS product electrical performances. A CAD bottom-up approach will be proposed and analyzed, based on the Design–in Reliability (DiR) methodology. With this purpose, a detailed analysis of the NBTI and the HC behaviours and their impact at different abstraction level is provided throughout this thesis. First, a physical framework presenting the NBTI and the HC mechanisms is given, focusing on electrical parameters weakening of nMOS and pMOS transistors. Moreover, the main analytical HC and NBTI degradation models are treated in details. In the second part, the delay degradation of digital standard cells due to NBTI, HCI is shown; an in-depth electrical CAD analysis illustrates the combined effects of design parameters and HCI/NBTI on the timing performance of standard cells. Additionally, a gate level approach is developed, in which HC and NBTI mechanisms are individually addressed. The consequences of the degradation at system level are presented in the third part of the thesis. With this objective, data extracted from silicon measures are compared against CAD estimations on two complexes IPs fabricated on STCMOS 45nm technologies. It is expected that the findings of this thesis highly contribute to the understanding of the NBTI and HC reliability wearout mechanisms at the system level.STAR

The HCI community is well aware of the gap between research and practice in the field. The issue is often discussed in terms of the applicability and adaption of theories and methods to the real world, but both categories seem insufficient for explaining how practitioners navigate the complexity of the problems they work on. This study takes a more fundamental perspective, inspired by theories of reflective practice and design. As a consequence, the attention is shifted to the framing of a problem that happens prior—or in parallel—to the use of theories and methods. Six case studies were collected through semi-structured interviews to investigate this position. The findings point towards a rather small set of techniques which are used for supporting the (re-)framing of a problem in an often pragmatic and informal way. A model locating the methods in their respective stages is proposed; and the methods are related to other research to suggest additional possibilities not mentioned by the participants of this study. What most clearly distinguished HCI practitioners from designers in other professions was their distrust in their own intuition, and the key role they attached to the user in response.

A recuperação de imagens baseada em conteúdo, amplamente conhecida como CBIR (do inglês Content-Based Image Retrieval), é um ramo da área da computação que vem crescendo muito nos últimos anos e vem contribuindo com novos desafios. Sistemas que utilizam tais técnicas propiciam o armazenamento e manipulação de grandes volumes de dados e imagens e processam operações de consultas de imagens a partir de características visuais extraídas automaticamente por meio de métodos computacionais. Esses sistemas devem prover uma interface de usuário visando uma interação fácil, natural e atraente entre o usuário e o sistema, permitindo que o usuário possa realizar suas tarefas com segurança, de modo eficiente, eficaz e com satisfação. Desse modo, o design da interface firma-se como um elemento fundamental para o sucesso de sistemas CBIR. Contudo, dentro desse contexto, a interface do usuário ainda é um elemento constituído de pouca pesquisa e desenvolvimento. Um dos obstáculos para eficácia de design desses sistemas consiste da necessidade em prover aos usuários uma interface de alta qualidade para permitir que o usuário possa consultar imagens similares a uma dada imagem de referência e visualizar os resultados. Para atingir esse objetivo, este trabalho visa analisar a interação do usuário em sistemas de recuperação de imagens por conteúdo e avaliar sua funcionalidade e usabilidade, aplicando técnicas de interação humano-computador que apresentam bons resultados em relação à performance de sistemas com grande complexidade, baseado em um estudo de caso aplicado à medicina / The content-based image retrieval (CBIR) is a challenging area of the computer science that has been growing in a very fast pace in the last years. CBIR systems employ techniques for extracting features from the images, composing the features vectores, and store them together with the images in data bases management system, allowing indexing and querying. CBIR systems deal with large volumes of images. Therefore, the feature vectors are extracted by automatic methods. These systems allow to query the images by content, processing similarity queries, which inherently demands user interaction. Consequently, CBIR systems must pay attention to the user interface, aiming at providing friendly, intuitive and attractive interaction, leading the user to do the tasks efficiently, getting the desired results, feeling safe and fulfilled. From the points highlighted beforehand, we can state that the human-computer interaction (HCI) is a key element of a CBIR system. However, there is still little research on HCI for CBIR systems. One of the requirements of HCI for CBIR is to provide a high quality interface to allow the user to search for similar images to a given query image, and to display the results properly, allowing further interaction. The present dissertation aims at analyzing the user interaction in CBIR systems specially suited to medical applications, evaluating their usability by applying HCI techniques. To do so, a case study was employed, and the results presented

Pervasive computing sa zameriava odstránenie zložitostí pri interakcii s výpočtovou technikou a zvýšenie efektivity pri jej každodennom používaní. Ale i po viac ako 15 rokoch od sformulovania hlavných cieľov Pervasive computingu existujú aspekty interakcie ktoré stále nie sú súčasťou užívateľskej skúsenosti s dnešnou technológiou. Bezproblémová integrácia s prostredím vedúca k technologickej neviditeľnosti, alebo interakcia naprieč rôznymi zariadeniami predstavujú stále veľkú výzvu. Hlavným cieľom tejto práce je prispieť k tomu, aby sa ciele Pervasive computingu priblížili k realizovaniu tým, že predstavíme spôsob intuitívneho zdieľania informácií medzi osobným a verejne umiestneným zariadením. Predstavili sme tri interakčné techniky, ktoré podporujú intuitívnu výmenu obsahu medzi osobným zariadením a zdieľaným displejom. Tieto techniky sú založené na prenose videa, rozšírenej realite a analýze pohľadových dát. Okrem interakčných techník sme tiež predstavili mechanizmus pre získavanie, prenos a rekonštrukciu aplikačného stavu na cieľovom zariadení.