The research proposes monitoring network traffic to preventing malicious attacks. It uses statistical theory and fuzzy control architecture to create a single transmission behavior. It will establish a normal transmis...
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The research proposes monitoring network traffic to preventing malicious attacks. It uses statistical theory and fuzzy control architecture to create a single transmission behavior. It will establish a normal transmission behavior module in order to achieve network monitoring and an alert mechanism. The mechanism tries to improve the abnormal behavior detection rate. The study is divided into three parts. The first part uses tools to simulate detection and aggressive behavior. According to many defensive measure reports, we will build a detection mechanism. The third part uses statistical theory and fuzzy control to monitor each network flow. The mechanism will preprocess denial of service attacks for an intrusion detection system.
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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The spread of telemedicine systems increases every day. The systems and PACS based on DICOM images has become common. This rise reflects the need to develop new storage systems, more efficient and with lower computati...
The spread of telemedicine systems increases every day. The systems and PACS based on DICOM images has become common. This rise reflects the need to develop new storage systems, more efficient and with lower computational costs. With this in mind, this article discusses a study for application in NetCDF data format as the basic platform for storage of DICOM images. The study case comparison adopts an ordinary database, the HDF5 and the NetCDF to storage the medical images. Empirical results, using a real set of images, indicate that the time to retrieve images from the NetCDF for large scale images has a higher latency compared to the other two methods. In addition, the latency is proportional to the file size, which represents a drawback to a telemedicine system that is characterized by a large amount of large image files.
Western blotting readily identifies specific proteins amidst complex biological backgrounds [1, 2]. Nevertheless, immunob-lotting suffers from tremendous labor-intensive and time-intensive requirements [3]. The slab-g...
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ISBN:
(纸本)9781618395955
Western blotting readily identifies specific proteins amidst complex biological backgrounds [1, 2]. Nevertheless, immunob-lotting suffers from tremendous labor-intensive and time-intensive requirements [3]. The slab-gel assays require 1-2 days for completion with multiple hands-on "blotting" steps and yield semi-quantitative information. Recently, our group has introduced new approaches for completing Western blotting. The microfluidic integration strategies introduced and used allow rapid results reporting, full assay automation, and limited sample consumption (1-10 uL). Our integration strategies use spatial, temporal, and spatiotemporal modulation of separation mechanisms in fully electrophoretic systems. The present study reports on recapitulation of immunoaffinity in previously sized proteins, using novel in-transit electrophoretic removal of SDS from SDS-protein complexes. Early results show both the length- and timescales for protein 'renaturation' are compatible with on-chip operation. Further, substantial binding affinity is recapitulated using this streamlined and promising approach.
Background: Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable prom...
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Background: Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG) algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. Results: We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, *** and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. Conclusions: We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the underlying network, and the applic
Telemedicine is a very important area in medical field that is expanding daily motivated by many researchers interested in improving medical applications. In Brazil was started in 2005, in the State of Santa Catarina ...
Telemedicine is a very important area in medical field that is expanding daily motivated by many researchers interested in improving medical applications. In Brazil was started in 2005, in the State of Santa Catarina has a developed server called the CyclopsDCMServer, which the purpose to embrace the HDF for the manipulation of medical images (DICOM) using a distributed file system. Since then, many researches were initiated in order to seek better performance. Our approach for this server represents an additional parallel implementation in I/O operations since HDF version 5 has an essential feature for our work which supports parallel I/O, based upon the MPI paradigm. Early experiments using four parallel nodes, provide good performance when compare to the serial HDF implemented in the CyclopsDCMServer.
Software Product Lines (SPLs) have been used to develop mobile and context-aware applications, which provide services and data for their users from anywhere and at any time using context information. In SPLs, commonal...
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Software Product Lines (SPLs) have been used to develop mobile and context-aware applications, which provide services and data for their users from anywhere and at any time using context information. In SPLs, commonality and variability of a system family are identified and often documented in a feature model. However, the development of a feature model for mobile and context-aware SPLs is not trivial, since it should comprise system and context information. Furthermore, the consistency check of feature models in the considered domain is also complex and demands advanced skills of software engineers. This paper proposes a mechanism to formalize and verify the correctness and consistency of feature models for mobile and context-aware SPLs based on a profile enriched with OCL specifications.
This paper presents a deterministic and adaptive spike model derived from radial basis functionsand a leaky integrate-and-fire sampler developed for training spiking neural networks without directweight manipulation. ...
This paper presents a deterministic and adaptive spike model derived from radial basis functions
and a leaky integrate-and-fire sampler developed for training spiking neural networks without direct
weight manipulation. Several algorithms have been proposed for training spiking neural networks
through biologically-plausible learning mechanisms, such as spike-timing-dependent synaptic plasticity
and Hebbian plasticity. These algorithms typically rely on the ability to update the synaptic strengths,
or weights, directly, through a weight update rule in which the weight increment can be decided
and implemented based on the training equations. However, in several potential applications of
adaptive spiking neural networks, including neuroprosthetic devices and CMOS/memristor nanoscale
neuromorphic chips, the weights cannot be manipulated directly and, instead, tend to change over time
by virtue of the pre- and postsynaptic neural activity. This paper presents an indirect learning method
that induces changes in the synaptic weights by modulating spike-timing-dependent plasticity by means
of controlled input spike trains. In place of the weights, the algorithm manipulates the input spike trains
used to stimulate the input neurons by determining a sequence of spike timings that minimize a desired
objective function and, indirectly, induce the desired synaptic plasticity in the network.
This paper presents an analysis of simultaneous temperature and electrical parameters measurements in a three phase induction motor (TIM). The electrical parameters, namely voltage and current in the motor windings, w...
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This paper presents an analysis of simultaneous temperature and electrical parameters measurements in a three phase induction motor (TIM). The electrical parameters, namely voltage and current in the motor windings, were measured with Hall effect sensors and the temperature in the stator slots were monitored using fiber Bragg grating sensors (FBG). In the performed temperature analysis, two sets of sensors were used, containing four FBG in each fiber. Eight FBG sensors were uniformly distributed in the TIM stator. A special encapsulation of the sensor was elaborated to minimize mechanical disturbances in the fiber due to motor operation. Tests were performed with motor running at no load and with intentional voltage disturbances in the windings produced at every 15 minutes periods. It was observed that the temperature distribution is not uniform in the TIM stator either with or without a balanced voltage in the windings. A mean level increase of 0.5°C in temperature was registered in all of the sensors when there is a lack of balance in the voltage windings.
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