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In this paper, we focus on weakly supervised referring expression comprehension (REC), and identify that the lack of fine-grained visual capability greatly limits the upper performance bound of existing methods. To address this issue, we propose a novel framework for weakly supervised REC, namely Dynamic Visual routing Network (DViN), which overcomes the visual shortcomings from the perspective of feature combination and alignment. In particular, DViN is equipped with a novel sparse routing mechanism to efficiently combine features of multiple visual encoders in a dynamic manner, thus improving the visual descriptive power. Besides, we further propose an innovative weakly supervised objective, namely Routing-based Feature Alignment (RFA), which facilitates the visual understanding of routed features through the intra-modal and inter-modal alignment. To validate DViN, we conduct extensive experiments on four REC benchmark datasets. Experiments demonstrate that DViN achieves state-of-the-art results on four benchmarks while maintaining competitive inference efficiency. Besides, the strong generalization ability of DViN is also validated on weakly supervised referring expression segmentation. Source codes are anonymously released at: https://github.com/XxFChen/DViN.

At the beginning of my internship, I was introduced to a few tools used at CERN. These tools include the HPCBatch cluster, where I was going to develop the project. The objective of the project is to study a new methodology of evaluating HPC clusters through simulations tools. Using simulation tools enable the possibility of knowing the cost-effectiveness and efficiency with precise results in advance. This methodology has the workflow shown below: 1. Obtain HPC application traces: by instrumenting applications using standard tools such as Score-P or Tau, we can generate detailed traces for each application. This way we can create a repository of HPC application traces. These can be generated by experts in the field. 2. Create simulation scenarios: by changing the component parameters, one can model faster CPUs or faster memory or storage according to the characteristics offered by vendors. 3. Explore cost-effective configurations: leveraging the application traces, we can use them as inputs for the simulator to evaluate different hypothetical scenarios. For instance, one where we invest more in a better network or a situation where we invest more in faster memory, or CPUs. Since the simulator has a graphical interface, this step (and the previous step) can be carried out by service managers, but also anybody in charge of resource procurement. Due to their expensiveness, knowing where the bottlenecks can be will save a lot of effort trying to optimize applications. Also, it can be useful by testing which applications are better for the existing HPC clusters, with the advantage of not having to saturate the cluster, delaying other possible results executing at that moment. This is applied either way to cloud environments and bare-metal.

<p>We have developed a software platform, ABAQUS (Automated Benchmarking of Algorithms for Quantum Systems), that can be used to benchmark the performance of both software frameworks and hardware devices used in the simulation of quantum computers. This platform has been developed as a Python package which can be easily extended with interfaces to any quantum software framework, on top of which the benchmarks implemented in the package can be run. What is more, these interfaces do not define or rely on the specific benchmarks that are run: these and their details are fully controlled by the ABAQUS package and they are common to all the frameworks.</p>\n\n<p>So far, ABAQUS incorporates some basic benchmarks based on random circuits, single-qubit and two-qubit gates and the Quantum Fourier Transform.</p>\n\n<p>In addition to this, we have designed a user-friendly web application in Flask that presents all the benchmark results in a clear and interactive manner. This web application is fully connected to the ABAQUS framework in such a way that any changes in ABAQUS are automatically reflected on the companion web application –– without any changes whatsoever on the web application source code.</p>

The Travelling Salesman Problem is a well-known problem where it is required to figure out the shortest route to visit all the stops. Even though it was formulated almost over a hundred years ago, nowadays it still has relevance and interest. Therefore, the attention throughout this paper was focused on the logistic computing relevant modification of the Travelling Salesman Problem called Travelling Holidayman Problem, which can be applicable in exploring and solving the current challenges of logistics. The problem of Travelling Holidayman is solved based on the greedy algorithm solver of the Travelling Salesman Problem. Even though the greedy algorithm shows the best performance in terms of time, it does not guarantee the optimality of the solution, that is to find the shortest path. Therefore, other approaches such as quantum computing should be considered in solving this problem.

The number of functionalities covered by the Oracle database increases from release to release. Thus also the possibilities to communicate with it from outside. More and more systems use HTTP requests in the form of REST API calls to interact with other systems. Through Oracle ORDS this communication is also possible to an Oracle database. This reduces the number of systems that need direct access to a database via a JDBC connector. In this project the creation of an ORDS module for a database schema is implemented and documented using the open-api standard. Subsequently, an application that previously required direct JDBC access to the database will be rewritten to enable communication with the resulting ORDS API.