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This paper tackles the issue of Data Centers (DCs) energy efficiency by proposing a Self-Adaptive Task Scheduler that proactively allocates incoming tasks to physical servers avoiding the need of consolidation and implicitly avoiding task migration from one server to another. The Self-Adaptive Task Scheduler is based on a MAPE architecture. The monitoring phase aggregates data about resource utilization,...
This work aims to apply visual-attention modeling to attention-based video compression. During our comparison we found that eye-tracking data collected even from a single observer outperforms existing automatic models by a significant margin. Therefore, we offer a semiautomatic approach: using computer-vision algorithms and good initial estimation of eye-tracking data from just one observer to produce...
Semantic gap, which is the difference between low-level image features and their high-level semantics, has become very popular and witnessed great interest in the last two decades. This paper deals with this problem and proposes a hybrid approach to learn image semantic concepts for modeling visual features in discriminative learning stage. It combines the advantages of human-in-the-loop and discriminative...
The main objective of this paper is the time-frequency analysis of the EEG signal captured in a cognitive task (i.e. object recognition) performed by human subjects. We investigate whether the power spectral density of the gamma frequency range can be used to classify the outcome of the object recognition task (i.e. seen, unseen, uncertain). The EEG signals were acquired and analyzed from 128 electrodes...
Despite the fact that cooperative localization approaches stand well in Wireless Sensor Networks (WSNs), they impose challenge of increased energy consumption resulting from the important communication overhead required to accomplish the localization task. In this paper, we developed an Energy Aware Cooperative Localization approach (EACL) based on using a recursive localization system. Obviously,...
Assisted living and home monitoring systems are gradually becoming a necessity, considering the current trends in population ageing and older adults' desire to continue living independently in their homes and their communities for as long as possible. This paper presents our current achievements regarding the implementation of a cyber-physical system for assisted living and home monitoring, developed...
Vehicle taillights detection is an important topic in collision avoidance and in the field of autonomous vehicles. Analyzing the behavior of the front vehicle can prevent possible accidents. In this paper, a method for detecting vehicle taillights is presented. First, the system detects vehicles and then searches for candidate taillight pairs inside the obtained vehicles. Two methods for detecting...
The ECSEL joint undertaking RobustSENSE focuses on technologies and solutions for automated driving in adverse weather conditions. One of the main technology challenges is to improve laser scanner performance in fog where the existing 905 nm LIDAR reliability degrades below tolerances. This report briefly summarizes the results of experimental fog absorbance measurements, which were conducted in test...
Software Defined Networking (SDN) is a new networking paradigm which provides better decoupling between control plane and data plane. The separation not only allows OpenFlow (OF) switches in the data plane simply to forward data, but also enables the centralized programmable controller to control the behavior of entire network. SDN makes it possible to manage the network more flexible and simple....
Numerous genetic algorithms with Pareto-ranking were proposed for solving multiobjective optimisations (MOOs). Mainly, these algorithms compute the fitness values of the solutions via dominance analysis. For few conflicting objectives, dominance analysis is suitable for managing the partial sorting; however, this technique is not capable to handle other common requirements of MOOs, such as preserving...
In this paper, a variant of the recently introduced whale optimization algorithm (WOA) was proposed based on adaptive switching of random walk per individual search agent. WOA is recently proposed bio-inspired optimizers that employ two different random walks. The original optimizer stochastically switches between the two random walk at each iteration regardless of the search agents performance and...
This paper presents the concepts of FPNA and FPNN, used for the approximation of artificial neural networks in FPGAs and introduces derived types of these concepts used by the authors. The process of transformation of a trained artificial neural network to an FPNN is described. The diagram of the FPGA implementation is presented. The results of experiments determining the approximation capabilities...
In this paper we present a method for generating healthy diets for elderly people. The method proposed is based on the Crab Mating Optimization Algorithm, which is inspired from the breeding behavior of crabs in nature. In our case the generated diet is composed of several meals per day and it can be created for a number of 7 days. In generating a healthy diet we have considered the elder's food preferences...
Regression testing is the testing activity performed after changes occurred on software. Its aim is to increase confidence that achieved software adjustments have no negative impact on the already functional parts of the software. Test case prioritization is one technique that could be applied in regression testing with the aim to find faults early, resulting in reduced cost and shorten time of testing...
State-of-the-art Low Level Virtual Machine (LLVM) compiler infrastructure has a dedicated set of optimizations for loops. Each optimization is organized as a separate pass in LLVM, whereas passes are created using a mix of object creational patterns. However, recent focus of modern compilers is in improving runtime performance using a large set of conservative optimizations, most often omitting the...
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