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A large class of motions can be decomposed into a movement task and null-space policy subject to a set of constraints. When learning such motions from demonstrations, we aim to achieve generalisation across different unseen constraints and to increase the robustness to noise while keeping the computational cost low. There exists a variety of methods for learning the movement policy and the constraints...
Wrench-based quality metrics play an important role in many applications such as grasp planning or grasp success prediction. In this work, we study the following discrepancy which is frequently overlooked in practice: the quality metrics are commonly computed under the assumption of sum-magnitude bounded contact forces, but the corresponding grasps are executed by a fully actuated device where the...
With the ubiquitous deployment of the mobile devices with increasingly better communication and computation capabilities, an emerging model called spatial crowdsourcing is proposed to solve the problem of unstructured big data by publishing location-based tasks to participating workers. However, massive spatial data generated by spatial crowdsourcing entails a critical challenge that the system has...
Energy efficiency in high performance computing (HPC) systems is a relevant issue nowadays, which is approached from multiple edges and components (network, I/O, resource management, etc). HPC industry turned its focus towards embedded and low-power computational infrastructures (of RISC architecture processors) to improve energy efficiency, therefore, we use an ARM-based cluster, known as millicluster,...
Cloud computing enables end users to execute high-performance computing applications by renting the required computing power. This pay-for-use approach enables small enterprises and startups to run HPC-related businesses with a significant saving in capital investment and a short time to market. When deploying an application in the cloud, the users may a) fail to understand the interactions of the...
Despite the fact that for the first time odd sets were mentioned in 1965, the theory of fuzzy sets does not lose its relevance. The fact that their values are combined into an infinite set allows more detailed description of the models and obtaining accurate data. The theory of fuzzy sets gives a lot of scope for creativity both in operator activity, namely in writing rules for logical-linguistic...
In recent years, there has been an increasing interest in music generation using machine learning techniques typically used for classification or regression tasks. This is a field still in its infancy, and most attempts are still characterized by the imposition of many restrictions to the music composition process in order to favor the creation of “interesting” outputs. Furthermore, and most importantly,...
Controlling the spread of infectious diseases in large populations is animportant societal challenge. Mathematically, the problem is best captured as acertain class of reaction-diffusion processes (referred to as contagionprocesses) over appropriate synthesized interaction networks. Agent-basedmodels have been successfully used in the recent past to study such contagionprocesses. We describe EpiSimdemics,...
Performance monitoring is essential for all subsystems, especially high performance computing systems. These systems are sensitive to errors and failures which lead to data losses and then severely impact on the organizations. Consequently, resource information in the systems (e.g., CPU usage, memory usage, disk I/O usage, etc.) during the operations must be collected through the system monitoring...
Predictive analysis methods offer the possibility ofestimating the impact of design decisions, which may help inthe accomplishment of operational optimal results, before thedeployment of the system, and therefore minimizing the requiredeffort and cost. However, current predictive methods cannot beused on cloud environments, because of their complexity anddynamic nature. The main goal of this thesis...
Recently, retail product recognition has become an interesting computer vision research topic. The classification of products on shelves is a very challenging classification problem because many product classes are visually similar in terms of shape, color, texture, and metric size. In shelves, same or similar products are more likely to appear adjacent to each other and displayed in certain arrangements...
Increasing volumes of data and the desire for realtime query capability make the development of efficient streaming algorithms for data analytics valuable. Streaming graph algorithms that avoid unnecessary recomputation through clever application of data dependency analysis are often more complex to derive than their static counterparts. This paper discusses a method to derive algorithms for streaming...
In this paper, we study the problem of predicting the visual quality of a specific test sample (e.g. a video clip) experienced by a specific user, based on the ratings by other users for the same sample and the same user for other samples. A simple linear model and algorithm is presented, where the characteristics of each test sample are represented by a set of parameters, and the individual preferences...
Nowadays, public bike-sharing systems are broadly adopted and deployed in many major cities, however, as public facilities, bicycles will be prone to damage and need to be replaced frequently, which results in high system maintenance costs. One of the root causes of bicycle damages is the serious load-unbalance of bicycle usage. In this paper, we propose a hybrid bicycle allocation strategy for bicycle...
Modelers face multiple challenges in their work. In this paper, we focus on two of them. First, multiple modeling methods and tools are currently available. Modelers are sometimes limited by their tools or paradigms. Second, when multiple models are proposed for the same case, a decision maker needs criteria to decide which model to choose for his/her objective.
Background modeling is a critical case for background-subtraction-based approaches and also for a wide range of applications. A background generation becomes difficult when the scene is complex or an object stay for more than half of the time in the scene. In this paper, we propose a block-based scene background initialization and modeling with low computational cost which making them feasible for...
Capturing technical and economic impacts of solar photovoltaics (PV) and other distributed energy resources (DERs) on electric distribution systems can require high-time resolution (e.g. 1 minute), long-duration (e.g. 1 year) simulations. However, such simulations can be computationally prohibitive, particularly when including complex control schemes in quasi-steady-state time series (QSTS) simulation...
Early design space evaluation of computer systems is usually performed using performance models (e.g., detailed simulators, RTL-based models, etc.). However, it is very challenging (often impossible) to run many emerging applications on detailed performance models owing to their complex software-stacks and long run times. To overcome such challenges in benchmarking these complex applications, we propose...
In this paper, we propose an interference-aware multicast routing scheme for a single-radio Wireless Mesh Networks carrying multiple multicast flows. We focus on multicast routing over WMNs with stationary nodes, such as community wireless networks. We present a new metric that is based on three components: Path Interference Cost (Ip), Broadcast Benefit Factor (BF), and Hop Count (HC). We proposed...
The dynamic nature of application workloads in modern MPSoC-based embedded systems is growing. To cope with the dynamism of application workloads at run time and to improve the efficiency of the underlying system architecture, this paper presents a novel run-time resource allocation algorithm for multimedia applications with the objective of minimizing energy consumption for predefined deadlines....
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