The idea of a Kripke semantics endowed with possibility/plausibility information is not new;in fact there are different approaches for that;see: [6], [13], [16], [19]. This paper follows the approach found in [6], but...
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In parallel programs, the tasks of a given application must cooperate in order to accomplish the required computation. However, the communication time between the tasks may be different depending on which core they ar...
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In parallel programs, the tasks of a given application must cooperate in order to accomplish the required computation. However, the communication time between the tasks may be different depending on which core they are executing and how the memory hierarchy and interconnection are used. The problem is even more important in multi-core machines with NUMA characteristics, since the remote access imposes high overhead, making them more sensitive to thread and data mapping. In this context, process mapping is a technique that provides performance gains by improving the use of resources such as interconnections, main memory and cache memory. The problem of detecting the best mapping is considered NP-Hard. Furthermore, in shared memory environments, there is an additional difficulty of finding the communication pattern, which is implicit and occurs through memory accesses. This work aims to provide a method for static mapping for NUMA architectures which does not require any prior knowledge of the application. Different metrics were adopted and an heuristic method based on the Edmonds matching algorithm was used to obtain the mapping. In order to evaluate our proposal, we use the NAS Parallel Benchmarks (NPB) and two modern multi-core NUMA machines. Results show performance gains of up to 75% compared to the native scheduler and memory allocator of the operating system.
Typical interaction designers which are not climate scientists, but interaction designers can make well-informed use of climate sciences and closely related sciences are discussed. Interaction design can make scientif...
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Typical interaction designers which are not climate scientists, but interaction designers can make well-informed use of climate sciences and closely related sciences are discussed. Interaction design can make scientific information, interpretations, and perspectives available in an accessible and widely distributed form so that people's consciousness is raised. Interaction design can help bridge the gap between scientific predictions and notions of certainty and uncertainty. The tipping point, by definition, is the point at which any efforts to stop something from happening arrive too late. The 2007 IPCC report predicts climate change will have massive implications for global food production and conditions of production, as well as for water, coastal habitations, health, and ecosystems. Such systems must make this information available at scale and in forms that are suitable to a number of different constituencies, individuals, policy makers, governments, and intergovernmental organizations.
This work proposes using a neural network with self organizing maps, to build a configuration policy, which enables the management of a supporting infrastructure for Web applications using virtual machines. The neural...
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This work proposes using a neural network with self organizing maps, to build a configuration policy, which enables the management of a supporting infrastructure for Web applications using virtual machines. The neural network classifies the cluster's operation states to perform configuration operations adding or subtracting resources from the cluster. The overall goal is to ensure quality of service required by the application, while trying to save energy, acting efficiently on physical servers (hosts) or manipulating the VMs. The work includes a performance evaluation carried out over a system implemented based on the proposed architecture.
A novel power-line interference(PLI) reduction algorithm is proposed as a pre-processing step for electrocardiogram(ECG) signals. A distinct feature of this proposed algorithm is its ability to detect the presence of ...
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A novel power-line interference(PLI) reduction algorithm is proposed as a pre-processing step for electrocardiogram(ECG) signals. A distinct feature of this proposed algorithm is its ability to detect the presence of PLI in the ECG signal before applying the PLI removal algorithm. A constant-false alarm rate(CFAR) PLI detector using a band-pass IIR notch filter is developed for this purpose. Once the presence of PLI is detected, a recursive least-squares(RLS) adaptive IIR filter then will be applied to eliminate the PLI anomaly. On the other hand, if the PLI is not detected, no PLI reduction filtering will be applied. The proposed intelligent algorithm is able to perform PLI reduction operation without human operator supervision. The proposed RLS adaptive notch filtering algorithm also exhibits fast convergence and numerical stability.
Emergency plans are fundamental for the speedy and effective response in disaster situations. Plans are often constructed by teams of experts, who apply their expertise to define response procedures, but lack part of ...
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Emergency plans are fundamental for the speedy and effective response in disaster situations. Plans are often constructed by teams of experts, who apply their expertise to define response procedures, but lack part of location-specific knowledge that can be very relevant to make decisions during responses. Such knowledge is, however, in the minds of people who use those spaces every day, but are not involved in the planning processes. In this paper, we advocate for citizens' involvement in emergency plan elaboration via Public Participation, a mechanism long time used in other areas of e-government. We define the steps of a collaborative process for the elicitation of citizen's knowledge via Public Participation. A summary of the results of an initial case study is used to demonstrate the feasibility of our proposal for improving emergency plans.
Organizations have been relying on collaboration for productivity improvement and knowledge sharing. The first step to foster collaboration in organizations is to make it explicit. With this aim, the Collaboration Mat...
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Organizations have been relying on collaboration for productivity improvement and knowledge sharing. The first step to foster collaboration in organizations is to make it explicit. With this aim, the Collaboration Maturity Model (CollabMM) was proposed and evaluated. The lessons learned during model applications in previous work pointed out the need to review both the model and its evaluation instruments. A literature review also showed some improvement opportunities. Therefore, the objective of this work is to develop a roadmap to highlight the main opportunities of evolution in CollabMM. These opportunities will compose our research agenda in this topic and guide future work.
The necessity of lowering the execution of system tests' cost is a consensual point in the software development community. The present study presents an optimization of the regression tests' activity, by adapt...
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We propose a novel optimization-based paradigm for designing enhanced classifiers. The proposed paradigm allows us to incorporate available prior process knowledge into classifier design, thereby improving the perform...
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We propose a novel optimization-based paradigm for designing enhanced classifiers. The proposed paradigm allows us to incorporate available prior process knowledge into classifier design, thereby improving the performance of the resulting classifiers. In this work, we focus on dynamical systems that can be represented as finite-state multi-dimensional stochastic processes that possess labeled steady-state distributions. Given prior operational knowledge of the process, our goal is to build a classifier that can accurately label future observations obtained from the steady-state, by utilizing both the available prior knowledge and the training data. Simulation results show that the proposed paradigm yields improved classifiers that outperform traditional classifiers that use only training data.
Identifying transcription factor binding sites (TFBSs) is crucial for understanding the mechanism of transcriptional regulation. It is known that transcription factors (TFs) often cooperate to regulate genes. While tr...
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Identifying transcription factor binding sites (TFBSs) is crucial for understanding the mechanism of transcriptional regulation. It is known that transcription factors (TFs) often cooperate to regulate genes. While traditional approaches can be used to discover binding motifs of a group of co-regulated genes, they often fail to accurately assign motifs to the corresponding TFs. Here, we consider two TFs together to infer their TFBSs and their synergistic relationship simultaneously. The basic idea is that if two TFs interact, their TFBSs, if distinct, would be conserved across species and coincided in the promoter regions of the genes they co-regulated. Applying our method to Saccharomyces cerevisiae chromatin immunoprecipitation data, we predicted 110 TF pairs with statistically significant motif assignments. A majority of these TF pairs have literature support to be synergistic, and the designated motifs to TFs match well with their known consensus. We further examined the synergism of predicted TF pairs in seven experimental conditions using ANOVA, and identified significant interactions.
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