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Automated Experiments on Ad Privacy Settings
A Tale of Opacity, Choice, and Discrimination

: Decision-oriented analysis of large data sets,” Ph.D. dissertation, Sever Institute of Washington University, 1992. [25] Alexa, “Is popularity in the top sites by category directory based on traffic rank?” https://support.alexa.com/hc/enus/ articles/200461970, accessed Nov. 21, 2014. [26] C. M. Bishop, Pattern Recognition and Machine Learning. Springer, 2006. [27] S. Holm, “A simple sequentially rejective multiple test procedure,” Scandinavian Journal of Statistics, vol. 6, no. 2, pp. 65-70, 1979. [28

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Pilot Study on the Application of Employee Scheduling for the Problem of Safety Instrumented System Design and Maintenance Planning for Remotely Located Oil and Gas Facilities

Abstract

The technology of production, transportation, and processing of oil and gas involves various hazardous processes. To mitigate the risk that these processes pose, the technological solutions work closely with the automated control and safety systems. The design and organisation of maintenance for the automated safety instrumented systems (SIS) have a significant bearing on the overall safety of operations in this industry. Over the past few decades, many hydrocarbon resources have been discovered in unconventional environments, such as remote, offshore, and arctic locations. Transportation of engineering personnel to these remote locations and back, and thereby, the organisation of the shift work poses additional challenges for the petroleum sector. Under such circumstances, the workforce-related costs play a considerable role in the overall cost of the technological solution and thereby the decisions regarding the workforce organisation should be addressed in the framework of evaluating and choosing the appropriate safety measures. That is why the research presented in this paper aims to address the lifecycle of the technological solution integrating the problems of SIS design, maintenance planning, and employee scheduling into a single decision-making framework to optimise the set of technical and organisational safety measures inherent in the SIS. The performance and maintenance of the SIS are described with a Markov model of device failures, repairs and technological incidents occurrence. The employee scheduling part of the mathematical model utilises the set-covering formulation of maintenance crews taking particular trips. A black-box optimisation algorithm is used to find reasonable solutions to the integrated problem of engineering design and workforce planning. The decisions include the choices of the components and structures for the safety system, the facility overhaul frequencies, the maintenance personnel size, as well as the schedules of trips and shifts for the crews.

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Machine–Learning in Optimization of Expensive Black–Box Functions

). A framework for evolutionary optimization with approximate fitness functions, IEEE Transactions on Evolutionary Computation 6 (5): 481–494. Jones, D.R., Schonlau, M. and Welch, W.J. (1998). Efficient global optimization of expensive black-box functions, Journal of Global Optimization 13 (4): 455–492. McKay, M.D., Beckman, R.J. and Conover, W.J. (1979). A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics 21 (2): 239

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Using Fitness Value for Monitoring Kiwifruit’s Variant Seedling in Tissue Culture

Penalty of Using Anonymous Dominant Markers (AFLPs, ISSRs, and RAPDs) for Phylogenetic Inference. - Molecular Phylogenetics and Evolution, Vol. 42, 2007, No 2, pp. 528-542. 5. Venkat, S. K., P. Bommisetty, M. S. Patil, L. Reddy, A. Chennareddy. The Genetic Linkage Maps of Anthurium Species Based on RAPD, ISSR and SRAP Markers. - Scientia Horticulturae, Vol. 178, 2014, pp. 132-137. 6. Kayis, S. A. Evaluation of Confidence Limit Estimates of Cluster Analysis on Molecular Marker Data. - Journal of the Science of Food and Agriculture, Vol. 92

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A metaheuristic for a numerical approximation to the mass transfer problem

Mathematical Modelling and Numerical Analysis 37(5): 851-868. Benamou, J. and Brenier, Y. (2000). A computational fluid mechanics solution to the Monge-Kantorovich mass transfer problem, Numerische Mathematik 84(3): 375-393. Bosc, D. (2010). Numerical approximation of optimal transport maps, SSRN Electronic Journal, DOI: 10.2139/ssrn.1730684. Caffarelli, L., Feldman, M. and McCann, R. (2002). Constructing optimal maps for Monge’s transport problem as a limit of strictly convex costs, Journal of the American Mathematical Society

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Facial Expression Recognition under Difficult Conditions: A Comprehensive Study on Edge Directional Texture Patterns

-learning in optimization of expensive black-box functions, International Journal of Applied Mathematics and Computer Science 27(1): 105-118, DOI: 10.1515/amcs-2017-0008. Uddin, M.Z., Lee, J.J. and Kim, T.S. (2009). An enhanced independent component-based human expression recognition from video, IEEE Transactions on Consumer Electronics 55(4): 2216-2224. Umbaugh, S.E. (2011). Digital Image Processing and Analysis, CRC Press, Boca Raton, FL. Valstar, M., Patras, I. and Pantic, M. (2005). Facial action unit detection using probabilistic actively

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ANFIS based prediction of the aluminum extraction from boehmite bauxite in the Bayer process

. Hydrometall. 59, 15-29. DOI: 10.1016/S0304-386X(00)00146-8. 14. Cao, S., Zhang, Y.F. & Zhang, Y. (2009). Preparation of sodium aluminate from the leach liquor of diaspoiric bauxite in concentration NaOH solution. Hydrometall. 98, 298-303. DOI:10.1016/j.hydromet.2009.05.016. 15. Đurić, I., Đorđević, P., Mihajlović, I., Nikolić, Đ. & Živković, Ž. (2010). Prediction of Al2O3 leaching recovery in the Bayer process using statistical multilinear regression analysis. J. Mining Metall. 46(2) B 161-169. DOI:10.2298/JMMB1002161D. 16

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Dropout Policy in Czech Higher Education: Can Universities Serve Several Masters?

Publishers. Brunsden, V., Davies, M., Shevlin, M., & Bracken, M. (2000). Why do HE Students Drop Out? A test of Tinto’s Model. Journal of Further and Higher Education, 24(1), 301-310. Bunge, M. (1963). A general black-box theory. Philosophy of Science, 30(4), 364-358. Cave, M. (1997). The use of performance indicators in higher education. A critical analysis of developing practice. London: Kingsley. Clark, B. R. (1997). Common problems and adaptive responses in the universities of the world: organizing for

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Your Choice MATor(s)
Large-scale Quantitative Anonymity Assessment of Tor Path Selection Algorithms Against Structural Attacks

380-389. ACM, 2009. [17] J. Feigenbaum, A. Johnson, and P. F. Syverson. Probabilistic Analysis of Onion Routing in a Black-Box Model. ACM Transactions on Information and System Security (TISSEC), 15(3):14, 2012. [18] N. Gelernter and A. Herzberg. On the limits of provable anonymity. In Proceedings of the 12th ACM workshop on Workshop on privacy in the electronic society, pages 225-236. ACM, 2013. [19] A. D. Jaggard, A. Johnson, P. Syverson, and J. Feigenbaum. Representing network trust and using it to improve anonymous

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Evolutionary Computing Based on QoS Oriented Energy Efficient VM Consolidation Scheme for Large Scale Cloud Data Centers

Software Engineering and Advanced Applications, Santander, Spain, 2013, pp. 357-364. 9. Farahnakian, F., T. Pahikkala et al. Energy Aware Consolidation Algorithm Based on K-Nearest Neighbor Regression for Cloud Data Centers. - In: Proc. of 6th IEEE/ACM International Conference on Utility and Cloud Computing, Dresden, Germany, 2013. 10. Wood, T., P. Shenoy et al. Sandpiper: Black-Box and Gray-Box Resource Management for Virtual Machines. - Computer Networks, Vol. 53, 2009, pp. 2923-2938. 11. Ajiro, Y., A. Tanaka. Improving

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