@conference {346,
	title = {Cyber Handyman and Nursing for Humanitarian Services and Disaster Relief},
	booktitle = {2018 IEEE International Symposium on Technologies for Homeland Security (HST)},
	year = {2018},
	month = {Oct},
	abstract = {<p>Calamities cause immense damage to the lives and properties; emergency management and humanitarian support have always been a challenge in the disaster-hit areas due to deficiency of skilled workforce and increase in demand for available experts. Not all the volunteers have the required technical expertise to handle those situations, utilizing the services of the remotely located experts to enhance the skills of the volunteers can help them to handle the situations efficiently. The existing communication mechanisms do not have the capabilities required for collaborating people over physical tasks, which is crucial during the emergency situations. In this paper, we present two novel remote collaboration systems, Cyber-Handyman and Cyber-Nurse using which the less-trained and inexperienced aid workers can enhance their capabilities with the help from remote experts. These units will be deployed in the disaster sites, and the remote experts access and control the sensors on it to guide the aid workers or the victims. The efficiency of the collaboration over physical tasks, which is vital during emergency situations, depends on the complexity of the protocols utilized and the efficiency of the collaboration system. We also propose a methodology to evaluate the protocol complexity and efficiency of the system. Our experiments and results show that with our collaboration system a remote helper can successfully guide the workers in performing a physical task with minimum difficulty.</p>
},
	keywords = {Collaboration, collaboration system, common grounding, Complexity theory, Entropy, Grounding, helper-worker collaboration, human-human collaboration, human-machine collaboration, protocol complexity theory, Protocols, remote collaboration, Senior citizens, Task analysis, voice over IP},
	doi = {10.1109/THS.2018.8574176},
	author = {Jonnada, Srikanth and Ram Dantu and Ranasinghe, Ishan}
}
@article {26,
	title = {An Impatient Evolutionary Algorithm With Probabilistic Tabu Search for Unified Solution of Some NP-Hard Problems in Graph and Set Theory via Clique Finding},
	journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
	volume = {38},
	year = {2008},
	pages = {645 - 666},
	abstract = {<p>Many graph- and set-theoretic problems, because of their tremendous application potential and theoretical appeal, have been well investigated by the researchers in complexity theory and were found to be NP-hard. Since the combinatorial complexity of these problems does not permit exhaustive searches for optimal solutions, only near-optimal solutions can be explored using either various problem-specific heuristic strategies or metaheuristic global-optimization methods, such as simulated annealing, genetic algorithms, etc. In this paper, we propose a unified evolutionary algorithm (EA) to the problems of maximum clique finding, maximum independent set, minimum vertex cover, subgraph and double subgraph isomorphism, set packing, set partitioning, and set cover. In the proposed approach, we first map these problems onto the maximum clique-finding problem (MCP), which is later solved using an evolutionary strategy. The proposed impatient EA with probabilistic tabu search (IEA-PTS) for the MCP integrates the best features of earlier successful approaches with a number of new heuristics that we developed to yield a performance that advances the state of the art in EAs for the exploration of the maximum cliques in a graph. Results of experimentation with the 37 DIMACS benchmark graphs and comparative analyses with six state-of-the-art algorithms, including two from the smaller EA community and four from the larger metaheuristics community, indicate that the IEA-PTS outperforms the EAs with respect to a Pareto-lexicographic ranking criterion and offers competitive performance on some graph instances when individually compared to the other heuristic algorithms. It has also successfully set a new benchmark on one graph instance. On another benchmark suite called Benchmarks with Hidden Optimal Solutions, IEA-PTS ranks second, after a very recent algorithm called COVER, among its peers that have experimented with this suite.</p>
},
	keywords = {Algorithm design and analysis, Clique finding, combinatorial complexity, Complexity theory, computational complexity, evolutionary algorithm, evolutionary algorithms (EAs), evolutionary computation, genetic algorithm, Genetic algorithms, graph theory, Heuristic algorithms, maximum clique finding, metaheuristic global optimization method, NP-hard problem, NP-hard problems in set and graph theory, optimisation, Pareto analysis, Performance analysis, probabilistic tabu search, probability, search problems, set theory, simulated annealing},
	doi = {10.1109/TSMCB.2008.915645},
	author = {Guturu, Parthasarathy and Ram Dantu}
}
