Report on a Boston University Conference December 7-8, 2012 on 'How Can the History and Philosophy of Science Contribute to Contemporary U.S. Science Teaching?'

This is an editorial report on the outcomes of an international conference sponsored by a grant from the National Science Foundation (NSF) (REESE-1205273) to the School of Education at Boston University and the Center for Philosophy and History of Science at Boston University for a conference titled: How Can the History and Philosophy of Science Contribute to Contemporary U.S. Science Teaching? The presentations of the conference speakers and the reports of the working groups are reviewed. Multiple themes emerged for K-16 education from the perspective of the history and philosophy of science. Key ones were that: students need to understand that central to science is argumentation, criticism, and analysis; students should be educated to appreciate science as part of our culture; students should be educated to be science literate; what is meant by the nature of science as discussed in much of the science education literature must be broadened to accommodate a science literacy that includes preparation for socioscientific issues; teaching for science literacy requires the development of new assessment tools; and, it is difficult to change what science teachers do in their classrooms. The principal conclusions drawn by the editors are that: to prepare students to be citizens in a participatory democracy, science education must be embedded in a liberal arts education; science teachers alone cannot be expected to prepare students to be scientifically literate; and, to educate students for scientific literacy will require a new curriculum that is coordinated across the humanities, history/social studies, and science classrooms.Comment: Conference funded by NSF grant REESE-1205273. 31 page

SCOR: Software-defined Constrained Optimal Routing Platform for SDN

A Software-defined Constrained Optimal Routing (SCOR) platform is introduced as a Northbound interface in SDN architecture. It is based on constraint programming techniques and is implemented in MiniZinc modelling language. Using constraint programming techniques in this Northbound interface has created an efficient tool for implementing complex Quality of Service routing applications in a few lines of code. The code includes only the problem statement and the solution is found by a general solver program. A routing framework is introduced based on SDN's architecture model which uses SCOR as its Northbound interface and an upper layer of applications implemented in SCOR. Performance of a few implemented routing applications are evaluated in different network topologies, network sizes and various number of concurrent flows.Comment: 19 pages, 11 figures, 11 algorithms, 3 table

Hyperparameters analysis of long short-term memory architecture for crop classification

Deep learning (DL) has seen a massive rise in popularity for remote sensing (RS) based applications over the past few years. However, the performance of DL algorithms is dependent on the optimization of various hyperparameters since the hyperparameters have a huge impact on the performance of deep neural networks. The impact of hyperparameters on the accuracy and reliability of DL models is a significant area for investigation. In this study, the grid Search algorithm is used for hyperparameters optimization of long short-term memory (LSTM) network for the RS-based classification. The hyperparameters considered for this study are, optimizer, activation function, batch size, and the number of LSTM layers. In this study, over 1,000 hyperparameter sets are evaluated and the result of all the sets are analyzed to see the effects of various combinations of hyperparameters as well the individual parameter effect on the performance of the LSTM model. The performance of the LSTM model is evaluated using the performance metric of minimum loss and average loss and it was found that classification can be highly affected by the choice of optimizer; however, other parameters such as the number of LSTM layers have less influence

A Phase-Type Distribution for the Sum of Two Concatenated Markov Processes Application to the Analysis Survival in Bladder Cancer

[EN] Stochastic processes are useful and important for modeling the evolution of processes that take different states over time, a situation frequently found in fields such as medical research and engineering. In a previous paper and within this framework, we developed the sum of two independent phase-type (PH)-distributed variables, each of them being associated with a Markovian process of one absorbing state. In that analysis, we computed the distribution function, and its associated survival function, of the sum of both variables, also PH-distributed. In this work, in one more step, we have developed a first approximation of that distribution function in order to avoid the calculation of an inverse matrix for the possibility of a bad conditioning of the matrix, involved in the expression of the distribution function in the previous paper. Next, in a second step, we improve this result, giving a second, more accurate approximation. Two numerical applications, one with simulated data and the other one with bladder cancer data, are used to illustrate the two proposed approaches to the distribution function. We compare and argue the accuracy and precision of each one of them by means of their error bound and the application to real data of bladder cancer.This paper has been supported by the Generalitat Valenciana grant AICO/2020/114.García Mora, MB.; Santamaria Navarro, C.; Rubio Navarro, G. (2020). A Phase-Type Distribution for the Sum of Two Concatenated Markov Processes Application to the Analysis Survival in Bladder Cancer. Mathematics. 8(12):1-15. https://doi.org/10.3390/math8122099S115812Rodríguez, J., Lillo, R. E., & Ramírez-Cobo, P. (2015). Failure modeling of an electrical N-component framework by the non-stationary Markovian arrival process. Reliability Engineering & System Safety, 134, 126-133. doi:10.1016/j.ress.2014.10.020García‐Mora, B., Santamaría, C., & Rubio, G. (2020). Markovian modeling for dependent interrecurrence times in bladder cancer. Mathematical Methods in the Applied Sciences, 43(14), 8302-8310. doi:10.1002/mma.6593Montoro-Cazorla, D., & Pérez-Ocón, R. (2014). Matrix stochastic analysis of the maintainability of a machine under shocks. Reliability Engineering & System Safety, 121, 11-17. doi:10.1016/j.ress.2013.07.002Fackrell, M. (2008). Modelling healthcare systems with phase-type distributions. Health Care Management Science, 12(1), 11-26. doi:10.1007/s10729-008-9070-yGarg, L., McClean, S., Meenan, B. J., & Millard, P. (2011). Phase-Type Survival Trees and Mixed Distribution Survival Trees for Clustering Patients’ Hospital Length of Stay. Informatica, 22(1), 57-72. doi:10.15388/informatica.2011.314Marshall, A. H., & McClean, S. I. (2003). Conditional phase-type distributions for modelling patient length of stay in hospital. International Transactions in Operational Research, 10(6), 565-576. doi:10.1111/1475-3995.00428Marshall, A. H., & McClean, S. I. (2004). Using Coxian Phase-Type Distributions to Identify Patient Characteristics for Duration of Stay in Hospital. Health Care Management Science, 7(4), 285-289. doi:10.1007/s10729-004-7537-zFackrell, M. (2012). A semi-infinite programming approach to identifying matrix-exponential distributions. International Journal of Systems Science, 43(9), 1623-1631. doi:10.1080/00207721.2010.549582García-Mora, B., Santamaría, C., Rubio, G., & Pontones, J. L. (2013). Computing survival functions of the sum of two independent Markov processes: an application to bladder carcinoma treatment. International Journal of Computer Mathematics, 91(2), 209-220. doi:10.1080/00207160.2013.765560Kenney, C., & Laub, A. J. (1989). Condition Estimates for Matrix Functions. SIAM Journal on Matrix Analysis and Applications, 10(2), 191-209. doi:10.1137/0610014Jackson, C. H. (2011). Multi-State Models for Panel Data: ThemsmPackage forR. Journal of Statistical Software, 38(8). doi:10.18637/jss.v038.i08Mullin, L., & Raynolds, J. (2014). Scalable, Portable, Verifiable Kronecker Products on Multi-scale Computers. Studies in Computational Intelligence, 111-129. doi:10.1007/978-3-319-04280-0_1