148 research outputs found
Residential Area Energy Consumption Big Data Analytics and Visualization
No full textA Master of Science thesis in Computer Engineering by Ragini Gupta entitled, “Residential Area Energy Consumption Big Data Analytics and Visualization”, submitted in June 2018. Thesis advisor is Dr. Abdulrehman Al-Ali and thesis co-advisor is Dr. Imran Zualkernan. Soft and hard copy available.As Internet of Things (IoT) technology and open source file distributed system applications are evolving, home appliances can be monitored and controlled via an IoT-based home gateway. These gateways collect energy consumption from home appliances and hence create a large amount of data. Due to the large amount of data being generated, utility companies require platforms that enable them to store, process, analyze, visualize, and monetize the energy consumption data, and to gain meaningful insights into load profiles. This thesis proposes a residential area smart energy management system that enables home owners and utilities to monitor consumption patterns of each home, community, state, and country. Using an open source file distributed file system tools, home owners can monitor their home appliances energy consumption on a periodic basis. Additionally, utilities can also monitor the neighborhoods, communities, states, and country’s consumption. The architecture was tested to process data from one million smart meters. This data was synthetically generated based on one year of real consumption data from a home. The big data was stored in a Hadoop cluster of four nodes. Dimensional modeling was used to develop benchmarking queries to create a real time dashboard consisting of charts, graphs, and reports for home owners and utilities. Both Spark and Hive were used to implement the benchmarking queries and it was found that Spark outperformed Hive in terms of latency and processor throughput. Spark’s average latency was fifteen minutes with an average throughput of 2400 MBps while Hive’s average latency was thirty-four minutes with an average throughput of 2200 MBps for processing one million smart meters in a four nodes cluster. To validate the proposed system outcomes, the results were compared with existing proprietary tools such as IBM’s TimeSeries and relational database management systems. Spark and Hive have an intermediate performance in comparison to IBM’s proprietary tool and relational database management system. The results demonstrate that the proposed solution can be utilized to provide energy data consumption visualization for consumer and utility provider stakeholders, while implementing Spark as the backend processing engine for low latency, performance gain, and a high throughput.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE
Emotional intelligence: exploring the road beyond personality and cognitive intelligence
No full textEmotional intelligence research holds a popular status in current academic and business community. However, emotional intelligence as an independent construct has been debatable with regard to its theoretical and empirical significance ever since it was introduced. Furthermore, conceptual and operational definitions, measuring instruments and questionable validity and subsequent results are highly diverse and even contradictory. In an attempt to bring coherence to the diffuse body of literature on emotional intelligence, we argue how emotional intelligence is different from personality and cognitive intelligence. In light of this, the current paper has discussed previous research findings to gain more insights about emotional intelligence accounting for variance in outcomes not explained by personality and cognitive intelligence. The extant literature review has guided us to conclude that emotional intelligence is a unique construct, distinct from personality and cognitive intelligence. Scope for future research in the emotional intelligence field is also suggested
A Framework for Data Quality for Synthetic Information
No full textData quality has been an area of increasing interest for researchers in recent years due to the rapid emergence of 'big data' processes and applications. In this work, the data quality problem is viewed from the standpoint of synthetic information. Based on the structure and complexity of synthetic data, a need to have a data quality framework specific to it was realized. This thesis presents this framework along with implementation details and results of a large synthetic dataset to which the developed testing framework is applied. A formal conceptual framework was designed for assessing data quality of synthetic information. This framework involves developing analytical methods and software for assessing data quality for synthetic information. It includes dimensions of data quality that check the inherent properties of the data as well as evaluate it in the context of its use. The framework developed here is a software framework which is designed considering software design techniques like scalability, generality, integrability and modularity. A data abstraction layer has been introduced between the synthetic data and the tests. This abstraction layer has multiple benefits over direct access of the data by the tests. It decouples the tests from the data so that the details of storage and implementation are kept hidden from the user. We have implemented data quality measures for several quality dimensions: accuracy and precision, reliability, completeness, consistency, and validity. The particular tests and quality measures implemented span a range from low-level syntactic checks to high-level semantic quality measures. In each case, in addition to the results of the quality measure itself, we also present results on the computational performance (scalability) of the measure.Master of Scienc
Changing trend in susceptibility to vancomycin of methicillin susceptible and resistant Staphylococcus aureus clinical isolates from a tertiary care centre
No full textThinking with an Accent
No full textThinking with an Accent casts accent as a powerfully coded yet underexplored mode of perception shaping our global cultural economy. Theorizing accent as a mediatized object, an interdisciplinary method, and an embodied practice, this volume invites readers to think with an accent—to practice a dialogical, multisensorial inquiry that can yield transformative modalities of knowledge, action, and care.
“There is no such thing as a voice without an accent, yet theories of voice still treat accents as the exception. Thinking with an Accent teaches us how to begin from accented voices and provides a panoply of tools for imagining, working with, building on, analyzing, and desiring accents.” — JONATHAN STERNE, author of Diminished Faculties: A Political Phenomenology of Impairment
“This creative and ambitious collection encourages us to reconsider our own accented lives and how they structure our social, digital, and literary worlds. An essential book.” — DOLORES INÉS CASILLAS, author of Sounds of Belonging: U.S. Spanish-Language Radio and Public Advocacy
“This book teaches us that the accent must be understood not as an ontological reality but as a co-constituted happening. The result is that accent becomes something to think with, not just to study. Straightforward, well argued, and a pleasure to read.” — KAREEM KHUBCHANDANI, author of Ishtyle: Accenting Gay Indian Nightlife
Thinking with an Accent
Get PDFThinking with an Accent casts accent as a powerfully coded yet underexplored mode of perception shaping our global cultural economy. Theorizing accent as a mediatized object, an interdisciplinary method, and an embodied practice, this volume invites readers to think with an accent—to practice a dialogical, multisensorial inquiry that can yield transformative modalities of knowledge, action, and care.
“There is no such thing as a voice without an accent, yet theories of voice still treat accents as the exception. Thinking with an Accent teaches us how to begin from accented voices and provides a panoply of tools for imagining, working with, building on, analyzing, and desiring accents.” — JONATHAN STERNE, author of Diminished Faculties: A Political Phenomenology of Impairment
“This creative and ambitious collection encourages us to reconsider our own accented lives and how they structure our social, digital, and literary worlds. An essential book.” — DOLORES INÉS CASILLAS, author of Sounds of Belonging: U.S. Spanish-Language Radio and Public Advocacy
“This book teaches us that the accent must be understood not as an ontological reality but as a co-constituted happening. The result is that accent becomes something to think with, not just to study. Straightforward, well argued, and a pleasure to read.” — KAREEM KHUBCHANDANI, author of Ishtyle: Accenting Gay Indian Nightlife
Leveraging Data Strategies for Shared Wellbeing: Family centered care for MI patients: Strategy for enhancing adherence to lifestyle modifications through remote patient management services
No full textThe main goal of this thesis is to create remote patient management (RPM) strategy to effectively involve patients’ families into e-health services, and promote the adoption and long-term adherence to lifestyle modifications of entire families. By exploring the potential of family-centered care ideology for healthcare delivery, this thesis paves a way to include family members of myocardial infarction(MI) patients as co-recipients of formal care. To accomplish the objective, various activities were undertaken, such as researching factors that influence healthcare paradigms, exploring effective strategies to promote healthy behavior, and investigating the role of family members in shaping a patient’s health trajectory.Through desk research and interviews with key-informants of cardiovascular and home based care, valuable insights were uncovered revealing the diverse roles family members can assume throughout a patient’s health journey. These roles were found to be dynamic and dependent on various factors including personal preferences and the stage in the health trajectory, highlighting the need for personalized healthcare approaches that cater to the unique preferences and dynamics of each family. Uncovering a research gap of the representation of these roles, a new perspective recognizing the perpetual influential capacity of family members was adopted to further explore individuals preferences of in their ability to be involved in the patients healthcare and to influence the health behaviour of the patient. By adopting this approach, family members are encouraged to prioritize their own health while simultaneously providing support to patients in maintaining positive lifestyle behaviors essential for sustaining cardiovascular health.Based on the insights gained from a qualitative study highlighting the differences in family contexts and subsequent preferences in health-oriented involvement, a service vision was formulated to demonstrate a family-centered healthcare delivery through a modular approach. The vision emphasized the importance of data-driven insights to inform tailored interventions for sustainable lifestyle adherence. By harnessing data, healthcare providers can gain valuable information about patients and family members, enabling them to tailor interventions and support structures to meet their specific needs.To move closer to this service vision, it is proposed to follow a data-enabled design process that enables human, technological and organizational considerations and thereby empowering designers to iterate and expand the service ecosystem. To conclude, this thesis creates an opportunity for engaging stakeholders and ensuring that the envisioned care approach aligns with the interconnected healthcare landscape, driving the system towards a more inclusive and comprehensive care future.Strategic Product Desig
Positive Affect as Mediator between Emotional Intelligence and Creativity: An Empirical Study from India
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