University of Texas at Arlington

About: University of Texas at Arlington is a education organization based out in Arlington, Texas, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 11758 authors who have published 28598 publications receiving 801626 citations. The organization is also known as: UT Arlington & University of Texas-Arlington.

Collaborative fixation: effects of others' ideas on brainstorming

Abstract: SUMMARY Three experiments examined whether or not fixation effects occur in brainstorming as a function of receiving ideas from others. Exchanging ideas in a groupreduced thenumber of domains ofideas that were explored by participants. Additionally, ideas given by brainstormers conformed to ideas suggested by other participants. Temporal analyses showed how the quantity, variety and novelty of ideas fluctuate over the course of a brainstorming session. Taking a break modulated the natural decline over time in the quantity and variety of ideas. Although fixation was observed in brainstorming in terms of conformity and restriction of the breadth of ideas, it did not influence the number of ideas generated in these experiments. Copyright # 2010 John Wiley & Sons, Ltd. Brainstorming is a popular method for group creativity, but is inefficient. In creative problem solving individuals often face fixation, an impediment to productive problem solving (Duncker, 1945; Luchins & Luchins, 1959; Maier, 1931). The present study investigated if fixation takes place in brainstorming and is a contributing factor to brainstorming’s inefficiency. Osborn (1957) believed that working in groups is more effective than working individually when using his rules. Those given his brainstorming rules generate more ideas than participants not given the rules (Parnes & Meadow, 1959). Theoretically, group brainstorming should be advantageous because it allows members to share ideas (Paulus, 2000). The larger the group, the more domains related to the problem should be accessed. Furthermore, each member will have a unique cognitive architecture and will synthesize ideas differently (Stasson & Bradshaw, 1995).

A Multiobjective Distributed Control Framework for Islanded AC Microgrids

Abstract: This paper proposes a distributed two-layer control structure for ac microgrids. Inverter-based distributed generators (DGs) can operate either as voltage-controlled voltage source inverters (VCVSI) or current-controlled voltage source inverters (CCVSI). VCVSIs provide the voltage and frequency support, whereas CCVSIs regulate the generated active and reactive powers. The proposed control structure has two main layers. The first layer deals with the voltage and frequency control of VCVSIs. The second layer regulates the active and reactive powers of CCVSIs. These controllers are implemented through two communication networks with one-way communication links and are fully distributed; each DG only requires its own information and the information of its neighbors on the communication network graph. The proposed control framework is verified on a microgrid test system and IEEE 34 test feeder.

A Comprehensive Study of the Past, Present, and Future of Data Deduplication

Abstract: Data deduplication, an efficient approach to data reduction, has gained increasing attention and popularity in large-scale storage systems due to the explosive growth of digital data. It eliminates redundant data at the file or subfile level and identifies duplicate content by its cryptographically secure hash signature (i.e., collision-resistant fingerprint), which is shown to be much more computationally efficient than the traditional compression approaches in large-scale storage systems. In this paper, we first review the background and key features of data deduplication, then summarize and classify the state-of-the-art research in data deduplication according to the key workflow of the data deduplication process. The summary and taxonomy of the state of the art on deduplication help identify and understand the most important design considerations for data deduplication systems. In addition, we discuss the main applications and industry trend of data deduplication, and provide a list of the publicly available sources for deduplication research and studies. Finally, we outline the open problems and future research directions facing deduplication-based storage systems.

Detection of False-Data Injection Attacks in Cyber-Physical DC Microgrids

Abstract: Power electronics-intensive dc microgrids use increasingly complex software-based controllers and communication networks. They are evolving into cyber-physical systems (CPS) with sophisticated interactions between physical and computational processes, making them vulnerable to cyber attacks. This paper presents a framework to detect possible false-data injection attacks (FDIAs) in cyber-physical dc microgrids. The detection problem is formalized as identifying a change in sets of inferred candidate invariants. Invariants are microgrids properties that do not change over time. Both the physical plant and the software controller of CPS can be described as Simulink/Stateflow (SLSF) diagrams. The dynamic analysis infers the candidate invariants over the input/output variables of SLSF components. The reachability analysis generates the sets of reachable states (reach sets) for the CPS modeled as hybrid automata. The candidate invariants that contain the reach sets are called the actual invariants. The candidate invariants are then compared with the actual invariants, and any mismatch indicates the presence of FDIA. To evaluate the proposed methodology, the hybrid automaton of a dc microgrid, with a distributed cooperative control scheme, is presented. The reachability analysis is performed to obtain the reach sets and, hence, the actual invariants. Moreover, a prototype tool, HYbrid iNvariant GEneratoR, is extended to instrument SLSF models, obtain candidate invariants, and identify FDIA.