In this thesis, the above-mentioned problem is addressed by building a middleware to facilitate reliable and flexible communications between two or more SCADA systems. Software Defined Networking (SDN), an emerging technology providing programmable networking, is introduced to assist the middleware. In traditional networks, network configurations required highly skilled personnel for configuring many network elements. However, SDN separates the control plane from the data plane, making network intelligence logically centralized, and leaving the forwarding switches with easy commands to follow. In this way, the underlying network infrastructures can be easily manipulated by programming, supporting the future dynamic network functions.
In this work, an SDN-assisted middleware is designed and implemented with open source platforms Open Network Operating System (ONOS) and Mininet, connecting the power grids emulator and water delivery and treatment system (WDTS) emulator EPANet. Since the focus of this work is on facilitating communications between dedicated networks, data transmissions in backbone networks are emulated. For the interfaces, a multithreaded communication module is developed. It not only enables real-time information exchange between two SCADA control centers but also supports multiple-to-multiple communications simultaneously. Human intervention is allowed in case of emergency.
SDN has many attractive benefits, however, there are still obstacles like high upgrade costs when implementing this technique. Therefore, rather than replace all the routers at once, incremental deployment of hybrid SDN networks consisting of both legacy routers and programmable SDN switches is adopted in this work. We emulate on the ratio of SDN deployment against the performance of the middleware and the results on the real dataset show that a higher fraction of SDN results in a higher reliability and flexibility of data transmissions. The middleware developed may contribute to the development of the next-generation SCADA systems.
While expert groups often make recommendations on a range of non-controversial as well as controversial issues, little is known about how the level of expert consensus-the level of expert agreement-influences perceptions of the recommendations. This research illustrates that for non-controversial issues expert groups that exhibit high levels of agreement are more persuasive than expert groups that exhibit low levels of agreement. This effect is mediated by the perceived entitativity-the perceived cohesiveness or unification of the group-of the expert group. But for controversial issues, this effect is moderated by the perceivers' implicit assumptions about the group composition. When perceivers are provided no information about a group supporting the Affordable Care Act-a highly controversial piece of U.S. legislation that is divided by political party throughout the country-higher levels of agreement are less persuasive than lower levels of agreement because participants assume there were more democrats and fewer republicans in the group. But when explicitly told that the group was half republicans and half democrats, higher levels of agreement are more persuasive.
Cancer therapy selects for cancer cells resistant to treatment, a process that is fundamentally evolutionary. To what extent, however, is the evolutionary perspective employed in research on therapeutic resistance and relapse? We analyzed 6,228 papers on therapeutic resistance and/or relapse in cancers and found that the use of evolution terms in abstracts has remained at about 1% since the 1980s. However, detailed coding of 22 recent papers revealed a higher proportion of papers using evolutionary methods or evolutionary theory, although this number is still less than 10%. Despite the fact that relapse and therapeutic resistance is essentially an evolutionary process, it appears that this framework has not permeated research. This represents an unrealized opportunity for advances in research on therapeutic resistance.