As large displays become more affordable, researchers investigate their productivity impacts and try to develop techniques for making the large display user experience more effective. Studies show that large displays enable users to create and manage more windows and engage in more complex multitasking behavior. Although recent work demonstrates significant productivity benefits of large shared displays, it shows numerous usability issues because current software design is not scaling well. Therefore, we took steps towards developing two user interface design guidelines for large shared displays. Specifically, empirical studies have been conducted to compare the effects of large shared display and personal display use. When each of them is used as a secondary display, large shared displays impose increased interruption and comprehension. Empirical and qualitative studies are designed to develop two user interface design guidelines for large shared displays. We designed a system called SuperTrack that uses a large shared display and the proposed guidelines to further enhance team efficiency and productivity in collaborative software development environments. Finally, an in-situ evaluation assesses the benefits of SuperTrack. Results show that exposing software development team members to a large shared display through SuperTrack leads to more communication among the members and improved group awareness — leading to increased productivity and efficiency. / Master of Science

The task of spectrum sensing, defined here to consist of signal detection, signal parameter estimation, and signal identification, is a critically important task in a wide-variety of wireless communication applications. For example, in recent years, government and research initiatives have proposed the idea of communication systems that could gain access to spectrum opportunistically when being unused by primary licensed spectrum users. In order for these opportunistic systems to be realizable, methods by which secondary spectrum users can detect and classify these primary users will be necessary. Furthermore, detection and classification among the secondary users themselves will be important for efficient spectrum usage in these systems. As another example, spectrum sensing is also of critical importance in many military applications. This is due to the inherent expectation that a priori information of hostile wireless systems will be minimal or unavailable. The goal of this dissertation is to provide both insight and solutions in the critical area of spectrum sensing. More specifically, the research contained within this dissertation deals with the development and analysis of spectrum sensing algorithms that address key issues related to channel and radio impairments that are at present underdeveloped in the literature. First, research is presented on a method-of-moments based signal parameter estimation and likelihood-based modulation classification approach for linear digital amplitude-phase modulated signals (PAM, PSK, QAM, ...) in slowly-varying flat-fading channels. Based on this work, research is then presented on a feature-based modulation classification approach which relaxes the requirements of perfect frequency synchronization and knowledge of the phase information of the received signal that the likelihood-based approach requires. Finally, research is presented on the impact that both sensor reliability and sensor correlation information have on collaborative signal detection and intelligent sensor selection. / Ph. D.

The Global Supply Chain Forum (Stanford Global Supply Chain Forum Web Resource, http://www.stanford.edu/groups/scforum) defines supply chain management (SCM) as “Supply chain management is the integration of key business processes from end user through original suppliers that provides products, services and information that add value for customer and other stakeholders.” The rapid development of the Internet has dramatically changed the traditional definitions of manufacturer, suppliers and customers. Newer approaches to supply chain management attempt to organize the supply chain as a network of cooperating intelligent agents, each performing one or more supply chain functions and each coordinating actions with one another. This research is aimed at creating a viable model of a single manufacturer single supplier collaborative supply chain system using a Vendor Managed Inventory (VMI) system. The research further uses known inventory performance parameters to performance benchmark the VMI system with traditional push-pull systems, develop a collaborative forecasting spreadsheet solution and a best alternative ordering policy amongst EOQ, Monthly, JIT and VMI policies under known lead time and a variety of demand distribution functions. / Master of Science

In today’s world, IoT systems are more and more overwhelming. All electronic devices are becoming connected. From lamps and refrigerators in smart homes, smoke detectors and cameras in monitoring systems, to scales and thermometers in healthcare systems, until phones, cars and watches in smart cities. All these connected devices generate a huge amount of data collected from the environment. To take advantage of these data, a processing phase is needed in order to extract useful information, allowing the best management of the system. Since most objects in IoT systems are resource limited, the processing step, usually performed by an artificial intelligence model, is offloaded to a more powerful machine such as the cloud server in order to benefit from its high storage and processing capacities. However, the cloud server is geographically remote from the connected device, which leads to a long communication delay and harms the effectiveness of the system. Moreover, due to the incredibly increasing number of IoT devices and therefore offloading operations, the load on the network has increased significantly. In order to benefit from the advantages of cloud based AIoT systems, we seek to minimize its shortcomings. In this thesis, we design a distributed architecture that allows combining these three domains while reducing latency and bandwidth consumption as well as the IoT device’s energy and resource consumption. Experiments conducted on different cloud based AIoT systems showed that the designed architecture is capable of reducing up to 80% of the transmitted data. / En el mundo actual, los sistemas de IoT (Internet de las cosas) son cada vez más abrumadores. Todos los dispositivos electrónicos se están conectando entre sí. Desde lámparas y refrigeradores en hogares inteligentes, detectores de humo y cámaras para sistemas de monitoreo, hasta básculas y termómetros para sistemas de atención médica, pasando por teléfonos, automóviles y relojes en ciudades inteligentes. Todos estos dispositivos conectados generan una enorme cantidad de datos recopilados del entorno. Para aprovechar estos datos, es necesario un proceso de análisis para extraer información útil que permita una gestión óptima del sistema. Dado que la mayoría de los objetos en los sistemas de IoT tienen recursos limitados, la etapa de procesamiento, generalmente realizada por un modelo de inteligencia artificial, se traslada a una máquina más potente, como el servidor en la nube, para beneficiarse de su alta capacidad de almacenamiento y procesamiento. Sin embargo, el servidor en la nube está geográficamente alejado del dispositivo conectado, lo que conduce a una larga demora en la comunicación y perjudica la eficacia del sistema. Además, debido al increíble aumento en el número de dispositivos de IoT y, por lo tanto, de las operaciones de transferencia de datos, la carga en la red ha aumentado significativamente. Con el fin de aprovechar las ventajas de los sistemas de AIoT (Inteligencia Artificial en el IoT) basados en la nube, buscamos minimizar sus desventajas. En esta tesis, hemos diseñado una arquitectura distribuida que permite combinar estos tres dominios al tiempo que reduce la latencia y el consumo de ancho de banda, así como el consumo de energía y recursos del dispositivo IoT. Los experimentos realizados en diferentes sistemas de AIoT basados en la nube mostraron que la arquitectura diseñada es capaz de reducir hasta un 80% de los datos transmitidos.

Evaluation is a process of investigating a project's implementation and results methodically and objectively. The evaluation problems in industry are extremely complicated and call for the examination of numerous qualitative and quantitative variables. Evaluators from different disciplines examine these variables. In order for the evaluators to collaborate during a broad evaluation process, there is a requirement for a collaborative evaluation methodology. In this research, a methodology for evaluation of any general application was implemented which is initially developed as part of a research effort supported by the Office of Naval Research. This technique is based on identifying the indicators to be applied in the evaluation of complex projects. In order to decrease complexity, these indicators are organized hierarchically which is modeled after the Analytic Hierarchy Process method. While at the top layer of this hierarchy is the subject we want to evaluate, towards the lower layers it is divided into more and more simple indicators. Therefore, the evaluators are responsible for assessing the project in terms of only the most simplified indicators. As a result, a precise evaluation which is not subject to human bias is accomplished. We have created a web-based application called Evaluator which allows the users to execute this methodology step by step. It simplifies the process by providing a user-friendly and easily accessible cloud-based platform in accordance with today's user experience principles. Although we have used this method and the software to evaluate projects, it is a tool that provides general usage for the assessment of a broad range of systems from various contexts. / Master of Science / Evaluation of a project is a process of systematic and objective assessment using a certain methodology. The evaluation problems we encounter in industry are quite complicated. This is due to the fact that a project must be evaluated in light of the numerous indicators it contains. Therefore, the project being assessed must be divided into these indicators as the first stage in the evaluation process. This layered form of the problem creates a hierarchical structure. Because the people who take part in evaluation are only capable of handling problems up to a certain level of complexity due to human nature. Therefore, it is essential to simplify problems to the point that those evaluating them can come to informed determinations. The strategy employed in this study makes it feasible to assess the primary subject of the evaluation effectively by limiting the evaluators to assessing only the most simplified indicators at the bottom of this hierarchy. This is the only task that the people in the evaluation process are responsible for. As a result, an accurate assessment not subject to human bias of error is achieved. We have created a web-based application called Evaluator which allows users to carry out this method's procedures. The user-friendly user interface of Evaluator makes it straightforward for people to take part in this complex process. Though we have used this approach and the software to assess projects, it is a flexible software which can be applied broadly for the assessment of a wide variety of systems from different contexts.

Two primary types of multiplayer gaming have emerged over the years. The first type involves co-located players on a shared display, and typically caps at four players. The second type of gaming provides a single display for each player. This type scales well beyond four players, but places no requirement on co-location. This paper will attempt to combine the best of both worlds via high-resolution, highly-multiplayer gaming. Over the past few years, there has been a rise in the number of extremely high-resolution, tiled displays. These displays provide an enormous amount of screen space to work with. This space was used to allow twelve co-located players to play a game together. This study accomplishes three things: we designed and built PyBomber, a high-resolution and highly multiplayer game for up to twelve players; secondly, user trials were conducted to see whether this type of gaming is enjoyable as well as to learn what sorts of social interactions take place amongst so many players; lastly, the lessons learned were generalized into design criteria for future high-resolution games. Results show that with more people, much more of the time during a game was filled with vocal interactions between players. There were also more physical movements in the larger games. Over the course of this study, we learned that good high-resolution games will: decide between a singular gameplay area and split views, use the physical space in front of the display, provide feedback that is localized to each player, and utilize input devices appropriately. / Master of Science

Skill sets such as understanding and applying computational concepts are essential prerequisites for success in the 21st century. One can learn computational concepts by taking a traditional course offered in a school or by self-guided learning through an online platform. Collaborative learning has emerged as an approach that researchers have found to be generally applicable and effective for teaching computational concepts. Rather than learning individually, collaboration can help reduce the anxiety level of learners, improve understanding and create a positive atmosphere to learning Computational Thinking (CT). There is, however, limited research focusing on how natural collaborative interactions among learners manifest during learning of computational concepts. Structured as a manuscript style dissertation, this doctoral study investigates three different but related aspects of novice learners collaboratively learning CT. The first manuscript (qualitative study) provides an overall understanding of the contextual factors and characterizes collaborative aspects of learning in a CT face-to-face classroom at a large Southeastern University. The second manuscript (qualitative study) investigates the social interaction occurring between group members of the same classroom. And the third manuscript (quantitative study) focuses on the relationship between different social interactions initiated by users and learning of CT in an online learning platform Scratch™. In the two diverse settings, Chi's (2009) Differentiated Overt Learning Activities (DOLA) has been used as a lens to better understand the significance of social interactions in terms of being active, constructive and interactive. Together, the findings of this dissertation study contribute to the limited body of CT research by providing insight on novice learner's attitude towards learning CT, collaborative moments of learning CT, and the differences in relationship between social interactions and learning CT. The identification of collaborative attributes of CT is expected to help educators in designing learning activities that facilitate such interactions within group of learners and look out for traits of such activities to assess CT in both classroom and online settings. / PHD / One of the overarching processes defining the future is the digital revolution, impinging on, reshaping, and transforming our personal and social lives. Computation is at the core of this change and is transforming how problems are defined, and solutions are found and implemented. Computer modeling, simulation and visualization software, Smart grid, and Software Defined Radio, are few examples where computation has allowed us to tackle problems from varied perspectives. Vast domains await discovery and mapping through creative processes of Computational Thinking (CT). CT is the thought process that enables us to effectively work in such a technology driven collaborative society. It provides us the ability to find the right technology for a problem and apply technology to resolve the problem. Skill sets such as understanding and applying computational concepts are essential prerequisites for success in the 21st century. One can learn CT by taking a traditional course offered in a school or by self-guided learning through an online platform. This doctoral study investigates three different but related aspects of how new learners are learning CT. The first qualitative study provides an overall understanding of circumstantial factors that influence the learning in a CT face-to-face classroom at a large Southeastern University. The second qualitative study investigates how students in groups (in the same classroom setting) can help each other to learn CT. And the third quantitative study focuses on users’ learning of CT in an online learning platform Scratch™. Together, the findings of this dissertation study contribute to the limited body of CT research by providing insight on new learner’s attitude towards learning CT, collaborative moments of learning CT, and the differences in the relationship between social interactions and learning CT. The identification of collaborative attributes of CT is expected to help educators in designing learning activities that facilitate such interactions within a group of learners and look out for traits of such activities to assess CT in both classroom and online settings.

The purpose of this study was to investigate teacher perceptions of Collaborative Inquiry embedded in a Professional Learning Community during departmental collaboration time and to explore the elements deemed most important to creating and/or maintaining this collaboration model at Lennox Charter High School. Teachers at Lennox Charter High School participated in this study. This mixed-methods case study triangulated survey, focus group, interview, and observation data to examine departmental collaboration and to define the elements most important to maintaining and improving Collaborative Inquiry at Lennox Charter High School. These elements were explored through the lens of research on Professional Learning Communities and Collaborative Inquiry. Specifically, data were examined with respect to the five themes of PLC work. These themes included context, challenge, capacity, commitments, and balancing content and process. A close examination of the data with respect to these themes revealed key take-aways for Lennox Charter High School; namely, that the school needed to bolster the data analysis aspect of Collaborative Inquiry, limit the scope of collaborative work, and endeavor to retain effective teachers so that teams had continuity and could more effectively engage veteran teachers in collaborative work. Using these recommendations would allow Lennox Charter High School to improve professional collaboration, engender meaningful teacher learning, and support equitable student achievement.

Yes / Based on their study of the food distribution supply chain, Can Eksoz and Dilek Önkal argue that the distributor has largely been overlooked in the principles we’ve created for collaborative demand and supply planning. Their article re-inserts the distributor into the supply chain and examines the challenges of collaboration from the distributor’s vantage point. This is a good lesson in how collaborative agreements must address the particular structures of the supply chain as well as the markets in which the supply-chain partners operate.

Yes / Team-Based Learning (TBL) is a collaborative learning model that refocuses classroom time to solving relevant problems instead of dispensing information. This is accomplished by a pre-class readiness assurance process that promotes accountability to self-directed learning and teamwork. While research related to the student experience with TBL is present in the literature, there is a relative lack of research published on the experiences of academic staff with TBL. Using a qualitative approach and a semi-structured interview format, this study explored the experiences of 26 academic staff in the UK who implemented TBL using a semi-structured interview format. Thematic analysis of interview text yielded five themes related to curriculum design, student outcomes, and the professional development of academic staff. / Supported by a grant from the Regis University Research and Scholarship Council.