The Digital Puglia Project: An Active Digital Library of Remote Sensing Data

The growing need of software infrastructure able to create, maintain and ease the evolution of scientific data, promotes the development of digital libraries in order to provide the user with fast and reliable access to data. In a world that is rapidly changing, the standard view of a digital library as a data repository specialized to a community of users and provided with some search tools is no longer tenable. To be effective, a digital library should be an active digital library, meaning that users can process available data not just to retrieve a particular piece of information, but to infer new knowledge about the data at hand. Digital Puglia is a new project, conceived to emphasize not only retrieval of data to the client's workstation, but also customized processing of the data. Such processing tasks may include data mining, filtering and knowledge discovery in huge databases, compute-intensive image processing (such as principal component analysis, supervised classification, or pattern matching) and on demand computing sessions. We describe the issues, the requirements and the underlying technologies of the Digital Puglia Project, whose final goal is to build a high performance distributed and active digital library of remote sensing data

Relativity in space-times with short-distance structure governed by an observer-independent (Planckian) length scale

I show that it is possible to formulate the Relativity postulates in a way that does not lead to inconsistencies in the case of space-times whose short-distance structure is governed by an observer-independent length scale. The consistency of these postulates proves incorrect the expectation that modifications of the rules of kinematics involving the Planck length would necessarily require the introduction of a preferred class of inertial observers. In particular, it is possible for every inertial observer to agree on physical laws supporting deformed dispersion relations of the type $E^2- c^2 p^2- c^4 m^2 + f(E,p,m;L_p)=0$, at least for certain types of $f$.Comment: Same formulas and results as in 1st version, but a change of notation is introduced in order to clarify that the studied illustrative example is consistent with the R.P. for both choices of the overall sign. 1 ref added and 2 refs upgraded. Some rewording of the text in Sec5, and addition of an analogy with background fields in ordinary electromagnetism which I use to illustrate difference between space-times with an observer-independent Lp, and space-times in which Lp is introduced without modifications of Special Relativit

Augmented Reality in Minimally Invasive Surgery

In the last 15 years Minimally Invasive Surgery, with techniques such as laparoscopy or endoscopy, has become very important and research in this field is increasing since these techniques provide the surgeons with less invasive means of reaching the patient’s internal anatomy and allow for entire procedures to be performed with only minimal trauma to the patient. The advantages of the use of this surgical method are evident for patients because the possible trauma is reduced, postoperative recovery is generally faster and there is less scarring. Despite the improvement in outcomes, indirect access to the operation area causes restricted vision, difficulty in hand-eye coordination, limited mobility handling instruments, two-dimensional imagery with a lack of detailed information and a limited visual field during the whole operation. The use of the emerging Augmented Reality technology shows the way forward by bringing the advantages of direct visualization (which you have in open surgery) back to minimally invasive surgery and increasing the physician's view of his surroundings with information gathered from patient medical images. Augmented Reality can avoid some drawbacks of Minimally Invasive Surgery and can provide opportunities for new medical treatments. After two decades of research into medical Augmented Reality, this technology is now advanced enough to meet the basic requirements for a large number of medical applications and it is feasible that medical AR applications will be accepted by physicians in order to evaluate their use and integration into the clinical workflow. Before seeing the systematic use of these technologies as support for minimally invasive surgery some improvements are still necessary in order to fully satisfy the requirements of operating physicians

NEMO-Med: Optimization and Improvement of Scalability

The NEMO oceanic model is widely used among the climate community. It is used with different configurations in more than 50 research projects for both long and short-term simulations. Computational requirements of the model and its implementation limit the exploitation of the emerging computational infrastructure at peta and exascale. A deep revision and analysis of the model and its implementation were needed. The paper describes the performance evaluation of the model (v3.2), based on MPI parallelization, on the MareNostrum platform at the Barcelona Supercomputing Centre. The analysis of the scalability has been carried out taking into account different factors, such as the I/O system available on the platform, the domain decomposition of the model and the level of the parallelism. The analysis highlighted different bottlenecks due to the communication overhead. The code has been optimized reducing the communication weight within some frequently called functions and the parallelization has been improved introducing a second level of parallelism based on the OpenMP shared memory paradigm

A Performance Evaluation Method for Climate Coupled Models

In the High Performance Computing context, the performance evaluation of a parallel algorithm is carried out mainly by considering the elapsed time for running the parallel application with both different number of cores and different problem sizes (for scaled speedup). Typically, parallel applications embed mechanisms to efficiently use the allocated resources, guaranteeing for example a good load balancing and reducing the parallel overhead. Unfortunately, this assumption is not true for coupled models. These models were born from the coupling of stand-alone climate models. The component models are developed independently from each other and they follow different development roadmaps. Moreover, they are characterized by different levels of parallelization as well as different requirements in terms of workload and they have their own scalability curve. Considering a coupled model as a single parallel application, we can note the lacking of a policy useful to balance the computational load on the available resources. This work tries to address the issues related to the performance evaluation of a coupled model as well as answering the following questions: once a given number of processors has been allocated for the whole coupled model, how does the run have to be configured in order to balance the workload? How many processors must be assigned to each of the component models? The methodology here described has been applied to evaluate the scalability of the CMCC-MED coupled model designed by the ANS Division of the CMCC. The evaluation has been carried out on two different computational architectures: a scalar cluster, based on IBM Power6 processors, and a vector cluster, based on NEC-SX9 processors

Data issues at the Euro-Mediterranean Centre for Climate Change

Climate Change research is even more becoming a data intensive and oriented scientific activity. Petabytes of climate data, big collections of datasets are continuously produced, delivered, accessed, processed by scientists and researchers at multiple sites at an international level. This work presents the Euro-Mediterranean Centre for Climate Change (CMCC) initiative, discussing data and metadata issues and dealing with both architectural and infrastructural aspects concerning the adopted grid enabled solution. A complete overview of the grid services deployed at the Centre is presented as well as the client side support (CMCC data portal and monitoring dashboard)

Optimal Task Mapping for NEMO Model

The climate numerical models require a considerable amount of computing power. The modern parallel architectures provide the needed computing power to perform scientific simulations at acceptable resolutions. However, the efficiency of the exploitation of the parallel architectures by the climate models is often poor. Several factors influence the parallel efficiency such as the parallel overhead due to the communications among concurrent tasks, the memory contention among tasks on the same computing node, the load balancing and the tasks synchronization. The work here described aims at addressing two of the factors influencing the efficiency: the communications and the memory contention. The used approach is based on the optimal mapping of the tasks on the SMP nodes of a parallel cluster. The best mapping can heavily influence the time spent for communications between tasks belonging to the same node either to different nodes. Moreover, if we consider that each parallel task will allocate different amount of memory, the optimal tasks mapping can balance the total amount of main memory allocated on the same node and hence reduce the overall memory contention. The climate model taken into consideration is PELAGOS025 made by coupling the NEMO oceanic model with the BFM biogeochemical model. It has been used in a global configuration with a horizontal resolution of 0.25◦. Three different mapping strategies have been implemented, analyzed and compared with the standard allocation performed by the local scheduler. The parallel architecture used for the evaluation is an IBM iDataPlex with Intel SandyBridge processors located at the CMCC’s Supercomputing Center

Advanced Visualization and Interaction Systems for Surgical Pre-operative Planning

The visualization of 3D models of the patient’s body emerges as a priority in surgery. In this paper two different visualization and interaction systems are presented: a virtual interface and a low cost multi-touch screen. The systems are able to interpret in real-time the user’s movements and can be used in the surgical pre-operative planning for the navigation and manipulation of 3D models of the human body built from CT images. The surgeon can visualize both the standard patient information, such as the CT image dataset, and the 3D model of the patient’s organs built from these images. The developed virtual interface is the first prototype of a system designed to avoid any contact with the computer so that the surgeon is able to visualize models of the patient’s organs and to interact with these, moving the finger in the free space. The multi-touch screen provides a custom user interface developed for doctors’ needs that allows users to interact, for surgical pre-operative planning purposes, both with the 3D model of the patient’s body built from medical images, and with the image dataset

An Ensemble Machine Learning Approach for Tropical Cyclone Detection Using ERA5 Reanalysis Data

Tropical Cyclones (TCs) are counted among the most destructive phenomena that can be found in nature. Every year, globally an average of 90 TCs occur over tropical waters, and global warming is making them stronger, larger and more destructive. The accurate detection and tracking of such phenomena have become a relevant and interesting area of research in weather and climate science. Traditionally, TCs have been identified in large climate datasets through the use of deterministic tracking schemes that rely on subjective thresholds. Machine Learning (ML) models can complement deterministic approaches due to their ability to capture the mapping between the input climatic drivers and the geographical position of the TC center from the available data. This study presents a ML ensemble approach for locating TC center coordinates, embedding both TC classification and localization in a single end-to-end learning task. The ensemble combines TC center estimates of different ML models that agree about the presence of a TC in input data. ERA5 reanalysis were used for model training and testing jointly with the International Best Track Archive for Climate Stewardship records. Results showed that the ML approach is well-suited for TC detection providing good generalization capabilities on out of sample data. In particular, it was able to accurately detect lower TC categories than those used for training the models. On top of this, the ensemble approach was able to further improve TC localization performance with respect to single model TC center estimates, demonstrating the good capabilities of the proposed approach.Comment: 27 pages, 8 figures, 1 table, submitted to Journal of Advances in Modeling Earth System