6 resultados para Relevance, IS Research, Focus Group, IS Success

em Digital Commons - Michigan Tech


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The Great Lakes watershed is home to over 40 million people, and the health of the Great Lakes ecosystem is vital to the overall economic, societal, and environmental health of the U.S. and Canada. However, environmental issues related to them are sometimes overlooked. Policymakers and the public face the challenges of balancing economic benefits with the need to conserve and/or replenish regional natural resources to ensure long term prosperity. From the literature review, nine critical stressors of ecological services were delineated, which include pollution and contamination, agricultural erosion, non-native species, degraded recreational resources, loss of wetlands habitat, climate change, risk of clean water shortage, vanishing sand dunes, and population overcrowding; this list was validated through a series of stakeholder discussions and focus groups in Grand Rapids. Focus groups were conducted in Grand Rapids to examine the awareness of, concern with, and willingness to expend resources on these stressors. Stressors that the respondents have direct contact with tend to be the most important. The focus group results show that concern related to pollution and contamination is much higher than for any of the other stressors. Low responses to climate change result in recommendations for outreach programs.

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As the demand for miniature products and components continues to increase, the need for manufacturing processes to provide these products and components has also increased. To meet this need, successful macroscale processes are being scaled down and applied at the microscale. Unfortunately, many challenges have been experienced when directly scaling down macro processes. Initially, frictional effects were believed to be the largest challenge encountered. However, in recent studies it has been found that the greatest challenge encountered has been with size effects. Size effect is a broad term that largely refers to the thickness of the material being formed and how this thickness directly affects the product dimensions and manufacturability. At the microscale, the thickness becomes critical due to the reduced number of grains. When surface contact between the forming tools and the material blanks occur at the macroscale, there is enough material (hundreds of layers of material grains) across the blank thickness to compensate for material flow and the effect of grain orientation. At the microscale, there may be under 10 grains across the blank thickness. With a decreased amount of grains across the thickness, the influence of the grain size, shape and orientation is significant. Any material defects (either natural occurring or ones that occur as a result of the material preparation) have a significant role in altering the forming potential. To date, various micro metal forming and micro materials testing equipment setups have been constructed at the Michigan Tech lab. Initially, the research focus was to create a micro deep drawing setup to potentially build micro sensor encapsulation housings. The research focus shifted to micro metal materials testing equipment setups. These include the construction and testing of the following setups: a micro mechanical bulge test, a micro sheet tension test (testing micro tensile bars), a micro strain analysis (with the use of optical lithography and chemical etching) and a micro sheet hydroforming bulge test. Recently, the focus has shifted to study a micro tube hydroforming process. The intent is to target fuel cells, medical, and sensor encapsulation applications. While the tube hydroforming process is widely understood at the macroscale, the microscale process also offers some significant challenges in terms of size effects. Current work is being conducted in applying direct current to enhance micro tube hydroforming formability. Initially, adding direct current to various metal forming operations has shown some phenomenal results. The focus of current research is to determine the validity of this process.

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The fields of Rhetoric and Communication usually assume a competent speaker who is able to speak well with conscious intent; however, what happens when intent and comprehension are intact but communicative facilities are impaired (e.g., by stroke or traumatic brain injury)? What might a focus on communicative success be able to tell us in those instances? This project considers this question in examining communication disorders through identifying and analyzing patterns of (dis) fluent speech between 10 aphasic and 10 non-aphasic adults. The analysis in this report is centered on a collection of data provided by the Aphasia Bank database. The database’s collection protocol guides aphasic and non-aphasic participants through a series of language assessments, and for my re-analysis of the database’s transcripts I consider communicative success is and how it is demonstrated during a re-telling of the Cinderella narrative. I conducted a thorough examination of a set of participant transcripts to understand the contexts in which speech errors occur, and how (dis) fluencies may follow from aphasic and non-aphasic participant’s speech patterns. An inductive mixed-methods approach, informed by grounded theory, qualitative, and linguistic analyses of the transcripts functioned as a means to balance the classification of data, providing a foundation for all sampling decisions. A close examination of the transcripts and the codes of the Aphasia Bank database suggest that while the coding is abundant and detailed, that further levels of coding and analysis may be needed to reveal underlying similarities and differences in aphasic vs. non-aphasic linguistic behavior. Through four successive levels of increasingly detailed analysis, I found that patterns of repair by aphasics and non-aphasics differed primarily in degree rather than kind. This finding may have therapeutic impact, in reassuring aphasics that they are on the right track to achieving communicative fluency.

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Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner. My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow patterns and how to pick good viewpoints to observe flow fields become critical. We treat streamline selection and viewpoint selection as symmetric problems and solve them simultaneously using the dual information channel [81]. To the best of my knowledge, this is the first attempt in flow visualization to combine these two selection problems in a unified approach. This work selects streamline in a view-independent manner and the selected streamlines will not change for all viewpoints. My another work [56] uses an information-theoretic approach to evaluate the importance of each streamline under various sample viewpoints and presents a solution for view-dependent streamline selection that guarantees coherent streamline update when the view changes gradually. When projecting 3D streamlines to 2D images for viewing, occlusion and clutter become inevitable. To address this challenge, we design FlowGraph [57, 58], a novel compound graph representation that organizes field line clusters and spatiotemporal regions hierarchically for occlusion-free and controllable visual exploration. We enable observation and exploration of the relationships among field line clusters, spatiotemporal regions and their interconnection in the transformed space. Most viewpoint selection methods only consider the external viewpoints outside of the flow field. This will not convey a clear observation when the flow field is clutter on the boundary side. Therefore, we propose a new way to explore flow fields by selecting several internal viewpoints around the flow features inside of the flow field and then generating a B-Spline curve path traversing these viewpoints to provide users with closeup views of the flow field for detailed observation of hidden or occluded internal flow features [54]. This work is also extended to deal with unsteady flow fields. Besides flow field visualization, some other topics relevant to visualization also attract my attention. In iGraph [31], we leverage a distributed system along with a tiled display wall to provide users with high-resolution visual analytics of big image and text collections in real time. Developing pedagogical visualization tools forms my other research focus. Since most cryptography algorithms use sophisticated mathematics, it is difficult for beginners to understand both what the algorithm does and how the algorithm does that. Therefore, we develop a set of visualization tools to provide users with an intuitive way to learn and understand these algorithms.

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In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.

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In recent years, security of industrial control systems has been the main research focus due to the potential cyber-attacks that can impact the physical operations. As a result of these risks, there has been an urgent need to establish a stronger security protection against these threats. Conventional firewalls with stateful rules can be implemented in the critical cyberinfrastructure environment which might require constant updates. Despite the ongoing effort to maintain the rules, the protection mechanism does not restrict malicious data flows and it poses the greater risk of potential intrusion occurrence. The contributions of this thesis are motivated by the aforementioned issues which include a systematic investigation of attack-related scenarios within a substation network in a reliable sense. The proposed work is two-fold: (i) system architecture evaluation and (ii) construction of attack tree for a substation network. Cyber-system reliability remains one of the important factors in determining the system bottleneck for investment planning and maintenance. It determines the longevity of the system operational period with or without any disruption. First, a complete enumeration of existing implementation is exhaustively identified with existing communication architectures (bidirectional) and new ones with strictly unidirectional. A detailed modeling of the extended 10 system architectures has been evaluated. Next, attack tree modeling for potential substation threats is formulated. This quantifies the potential risks for possible attack scenarios within a network or from the external networks. The analytical models proposed in this thesis can serve as a fundamental development that can be further researched.