A Framework for Genetic Algorithms Based on Hadoop

Genetic Algorithms (GAs) are powerful metaheuristic techniques mostly used in many real-world applications. The sequential execution of GAs requires considerable computational power both in time and resources. Nevertheless, GAs are naturally parallel and accessing a parallel platform such as Cloud is easy and cheap. Apache Hadoop is one of the common services that can be used for parallel applications. However, using Hadoop to develop a parallel version of GAs is not simple without facing its inner workings. Even though some sequential frameworks for GAs already exist, there is no framework supporting the development of GA applications that can be executed in parallel. In this paper is described a framework for parallel GAs on the Hadoop platform, following the paradigm of MapReduce. The main purpose of this framework is to allow the user to focus on the aspects of GA that are specific to the problem to be addressed, being sure that this task is going to be correctly executed on the Cloud with a good performance. The framework has been also exploited to develop an application for Feature Subset Selection problem. A preliminary analysis of the performance of the developed GA application has been performed using three datasets and shown very promising performance

Fitting the Continuum Component of A Composite SDSS Quasar Spectrum Using CMA-ES

Fitting the continuum component of a quasar spectrum in UV/optical band is challenging due to contamination of numerous emission lines. Traditional fitting algorithms such as the least-square fitting and the Levenberg-Marquardt algorithm (LMA) are fast but are sensitive to initial values of fitting parameters. They cannot guarantee to find global optimum solutions when the object functions have multiple minima. In this work, we attempt to fit a typical quasar spectrum using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). The spectrum is generated by composing a number of real quasar spectra from the Sloan Digital Sky Survey (SDSS) quasar catalog data release 3 (DR3) so it has a higher signal-to-noise ratio. The CMA-ES algorithm is an evolutionary algorithm that is designed to find the global rather than the local minima. The algorithm we implemented achieves an improved fitting result than the LMA and unlike the LMA, it is independent of initial parameter values. We are looking forward to implementing this algorithm to real quasar spectra in UV/optical band.Comment: 23 pages, 8 figures, 5 table

Optimizing Engagement Simulations Through the Advanced Framework for Simulation, Integration, and Modeling (AFSIM) Software

The ability to effectively model and simulate military missions holds the potential to save lives, money, and resources for the United States. The Advanced Framework for Simulation, Integration, and Modeling (AFSIM) software is a tool used to rapidly simulate and model new technologies and mission level scenarios. In this thesis, our objective is to integrate a closed loop optimization routine with AFSIM to identify an effective objective function to assess optimal inputs for engagement scenarios. Given the many factors which impact a mission level engagement, we developed a tool which interfaces with AFSIM to observe the effects from multiple inputs in an engagement scenario. Our tool operates under the assumption that simulation results have met an acceptable convergence threshold. The objective function evaluates the effectiveness and associated cost with a scenario using a genetic algorithm and a particle swarm optimization algorithm. From this, a statistical analysis was performed to assess risk from the distribution of effectiveness and cost at each point. The method allows an optimal set of inputs to be selected for a desired result from the selected engagement scenario.No embargoAcademic Major: Mechanical Engineerin

Postoffer Pre-Placement Screening for Carpal Tunnel Syndrome in Newly Hired Manufacturing Workers

OBJECTIVE: We determined the predictive validity of a post-offer pre-placement (POPP) screen using nerve conduction velocity studies (NCV) to identify future cases of carpal tunnel syndrome (CTS). METHODS: A cohort of 1648 newly hired manufacturing production workers underwent baseline NCS, and were followed for 5 years. RESULTS: There was no association between abnormal POPP NCV results and incident CTS. Varying NCV diagnostic cut-offs did not improve predictive validity. Workers in jobs with high hand/wrist exposure showed greater risk of CTS than those in low exposed jobs (Relative Risk 2.82; 95% CI 1.52, 5.22). CONCLUSIONS: POPP screening seems ineffective as a preventive strategy for CTS

Evolutionary improvement of programs

Most applications of genetic programming (GP) involve the creation of an entirely new function, program or expression to solve a specific problem. In this paper, we propose a new approach that applies GP to improve existing software by optimizing its non-functional properties such as execution time, memory usage, or power consumption. In general, satisfying non-functional requirements is a difficult task and often achieved in part by optimizing compilers. However, modern compilers are in general not always able to produce semantically equivalent alternatives that optimize non-functional properties, even if such alternatives are known to exist: this is usually due to the limited local nature of such optimizations. In this paper, we discuss how best to combine and extend the existing evolutionary methods of GP, multiobjective optimization, and coevolution in order to improve existing software. Given as input the implementation of a function, we attempt to evolve a semantically equivalent version, in this case optimized to reduce execution time subject to a given probability distribution of inputs. We demonstrate that our framework is able to produce non-obvious optimizations that compilers are not yet able to generate on eight example functions. We employ a coevolved population of test cases to encourage the preservation of the function's semantics. We exploit the original program both through seeding of the population in order to focus the search, and as an oracle for testing purposes. As well as discussing the issues that arise when attempting to improve software, we employ rigorous experimental method to provide interesting and practical insights to suggest how to address these issues

Bioresorbable Polylactide Interbody Implants in an Ovine Anterior Cervical Discectomy and Fusion Model: Three-Year Results

Study Design. In vivo study of anterior discectomy and fusion using a bioresorbable 70:30 poly(l-lactide-co-d,l-lactide) interbody implant in an ovine model. Objective. To evaluate the efficacy of the polylactide implant to function as an interbody fusion device, and to assess the tissue reaction to the material during the resorption process. Summary of Background Data. The use of polylactide as a cervical interbody implant has several potential advantages when compared with traditional materials. Having an elastic modulus very similar to bone minimizes the potential for stress shielding, and as the material resorbs additional loading is transferred to the developing fusion mass. Although preclinical and clinical studies have demonstrated the suitability of polylactide implants for lumbar interbody fusion, detailed information on cervical anterior cervical discectomy and fusion (ACDF) with polylactide devices is desirable. Methods. Single level ACDF was performed in 8 skeletally mature ewes. Bioresorbable 70:30 poly (l-lactide-co-d,l-lactide) interbody implants packed with autograft were used with single-level metallic plates. Radiographs were made every 3 months up to 1 year, and yearly thereafter. The animals were killed at 6 months (3 animals), 12 months (3 animals), and 36 months (2 animals). In addition to the serial plain radiographs, the specimens were evaluated by nondestructive biomechanical testing and undecalcified histologic analysis. Results. The bioresorbable polylactide implants were effective in achieving interbody fusion. The 6-month animals appeared fused radiographically and biomechanically, whereas histologic sections demonstrated partial fusion (in 3 of 3 animals). Radiographic fusion was confirmed histologically and biomechanically at 12 months (3 of 3 animals) and 36 months (2 of 2 animals). A mild chronic inflammatory response to the resorbing polylactide implant was observed at both 6 months and 12 months. At 36 months, the operative levels were solidly fused and the implants were completely resorbed. No adverse tissue response was observed in any animal at any time period. Conclusion. Interbody fusion was achieved using bioresorbable polylactide implants, with no evidence of implant collapse, extrusion, or adverse tissue response to the material. The use of polylactide as a cervical interbody device appears both safe and effective based on these ACDF animal model results

Building public-private partnerships for agricultural innovation:

Public-private partnerships are a new way of carrying out research and development (R&D) in Latin America's agricultural sector. These partnerships spur innovation for agricultural development and have various advantages over other institutional arrangements fostering R&D. This report summarizes the experiences of a research project that analyzed 125 public-private research partnerships (PPPs) in 12 Latin American countries. The analysis indicates that several types of partnerships have emerged in response to the various needs of the different partners. Nevertheless, public-private partnerships are not always the most appropriate mechanism by which to carry out R&D and foster innovation in agriculture. Sometimes, it is more efficient to organize research via participatory projects or through research contracts.Public-private partnerships, Agricultural innovations, Capacity strengthening, Agricultural research,