A General Simulation Framework for Supply Chain Modeling: State of the Art and Case Study

Nowadays there is a large availability of discrete event simulation software that can be easily used in different domains: from industry to supply chain, from healthcare to business management, from training to complex systems design. Simulation engines of commercial discrete event simulation software use specific rules and logics for simulation time and events management. Difficulties and limitations come up when commercial discrete event simulation software are used for modeling complex real world-systems (i.e. supply chains, industrial plants). The objective of this paper is twofold: first a state of the art on commercial discrete event simulation software and an overview on discrete event simulation models development by using general purpose programming languages are presented; then a Supply Chain Order Performance Simulator (SCOPS, developed in C++) for investigating the inventory management problem along the supply chain under different supply chain scenarios is proposed to readers.Comment: International Journal of Computer Science Issues online at http://ijcsi.org/articles/A-General-Simulation-Framework-for-Supply-Chain-Modeling-State-of-the-Art-and-Case-Study.ph

Draft Opinion of the European Economic and Social Committee on The European Citizens' Initiative (review)

Four years after the ECI regulation entered into force, the European Economic and Social Committee (EESC) points out that Europeans are at the heart of the European venture and this mechanism could help overcome the democratic deficit by promoting active citizenship and participatory democracy. In line with the views already voiced by the European Parliament, the Committee of the regions and the European Ombudsman, the EESC considers that the European citizens initiative has not achieved its full potential because of a regulation that should be revised

Sensitivity Analysis of a Bidirectional Wireless Charger for EV

Bidirectional chargers are required to fully integrate Electric Vehicle (EV) into the smart grids. Additionally, wireless chargers ease the charge/discharge process of the EV batteries so that they are becoming more popular to fulfill a V2G scenario. When considering the load of wireless chargers, it is a requirement to know the real output power that these systems offer. The designed output power may differ from the real one as components suffer from tolerance. This paper defines six sensitivity factors to model the severity of the effects of tolerance into the output power. To do so, an electric circuit analysis is used and a mathematical formulation is derived. The six sensitivity factors are computed for a laboratory prototype.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Highly luminescent perovskite–aluminum oxide composites

In this communication we report on the preparation of CH3NH3PbBr3 perovskite/Al2O3 nanoparticle composites in a thin film configuration and demonstrate their high photoluminescence quantum yield. The composite material is solution-processed at low temperature, using stable alumina nanoparticle dispersions. There is a large influence of the alumina nanoparticle concentration on the perovskite morphology and on its photoluminescence

Genetic Algorithm Modeling with GPU Parallel Computing Technology

We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel computing technology. The model was derived from a multi-core CPU serial implementation, named GAME, already scientifically successfully tested and validated on astrophysical massive data classification problems, through a web application resource (DAMEWARE), specialized in data mining based on Machine Learning paradigms. Since genetic algorithms are inherently parallel, the GPGPU computing paradigm has provided an exploit of the internal training features of the model, permitting a strong optimization in terms of processing performances and scalability.Comment: 11 pages, 2 figures, refereed proceedings; Neural Nets and Surroundings, Proceedings of 22nd Italian Workshop on Neural Nets, WIRN 2012; Smart Innovation, Systems and Technologies, Vol. 19, Springe

HE4 in the differential diagnosis of ovarian masses

Ovarian masses, a common finding among pre- and post-menopausal women, can be benign or malignant. Ovarian cancer is the leading cause of death from gynecologic malignancy among women living in industrialized countries. According to the current guidelines, measurement of CA125 tumor marker remains the gold standard in the management of ovarian cancer. Recently, HE4 has been proposed as emerging biomarker in the differential diagnosis of adnexal masses and in the early diagnosis of ovarian cancer. Discrimination of benign and malignant ovarian tumors is very important for correct patient referral to institutions specializing in care and management of ovarian cancer. Tumor markers CA125 and HE4 are currently incorporated into the Risk of Ovarian Malignancy Algorithm” (ROMA) with menopausal status for discerning malignant from benign pelvic masses. The availability of a good biomarker such as HE4, closely associated with the differential and early diagnosis of ovarian cancer, could reduce medical costs related to more expensive diagnostic procedures. Finally, it is important to note that HE4 identifies platinum non-responders thus enabling a switch to second line chemotherapy and improved survival

An analysis of feature relevance in the classification of astronomical transients with machine learning methods

The exploitation of present and future synoptic (multi-band and multi-epoch) surveys requires an extensive use of automatic methods for data processing and data interpretation. In this work, using data extracted from the Catalina Real Time Transient Survey (CRTS), we investigate the classification performance of some well tested methods: Random Forest, MLPQNA (Multi Layer Perceptron with Quasi Newton Algorithm) and K-Nearest Neighbors, paying special attention to the feature selection phase. In order to do so, several classification experiments were performed. Namely: identification of cataclysmic variables, separation between galactic and extra-galactic objects and identification of supernovae.Comment: Accepted by MNRAS, 11 figures, 18 page