the development of customized mobile applications basing on the composition mechanism (i.e. using existing software entities) has received a lot of attention in the last couple of years. The mobile devices heterogenei...
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ISBN:
(纸本)9781467376891
the development of customized mobile applications basing on the composition mechanism (i.e. using existing software entities) has received a lot of attention in the last couple of years. The mobile devices heterogeneity shows that the portability requirements play an important role in the mobile applications developpement domain. Otherwise, mobile applications strongly depend on the execution environment features. Thereby, in order to make sure the correct deployment and the proper functioning of the composite mobile application it is necessary to ensure that their constituents are adaptable to the current context of the mobile device. To cope with this issue and due to the fact that several software entities can be used to implement the identified requirements for a desired mobile application, we propose in this paper a context-driven selection algorithm that aims at selecting the adaptive software entities among all corresponding ones. Also, it targets to determine the different possible composition paths to build customized mobile applications. To achieve this objective, we propose ontology based descriptions to define the context of the corresponding software entities and the execution environment.
Uninformative biological variability elimination methods were studied in the near-infrared calibration model for predicting the soluble solids content of apples. Four different preprocessing methods, namely, Savitzky-...
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Uninformative biological variability elimination methods were studied in the near-infrared calibration model for predicting the soluble solids content of apples. Four different preprocessing methods, namely, Savitzky-Golay smoothing, multiplicative scatter correction, standard normal variate, and mean normalization, as well as their combinations were conducted on raw Fourier transformnear-infrared spectra to eliminate the uninformative biological variability. Subsequently, robust calibration models were established by using partial least squares regression analysis and wavelength selection algorithms. Results indicated that the partial least squares calibration models with characteristic variables selected by CARS method coupled with preprocessing of Savitzky-Golay smoothing and multiplicative scatter correction had a considerable potential for predicting apple soluble solids content regardless of the biological variability.
Extracting inherent patterns from large data using decompositions of data matrix by a sampled subset of exemplars has found many applications in machine learning. We propose a computationally efficient algorithm for a...
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ISBN:
(纸本)9781509041183
Extracting inherent patterns from large data using decompositions of data matrix by a sampled subset of exemplars has found many applications in machine learning. We propose a computationally efficient algorithm for adaptive exemplar sampling, called fast exemplar selection (FES). The proposed algorithm can be seen as an efficient variant of the oASIS algorithm [1]. FES iteratively selects incoherent exemplars based on the exemplars that are already sampled. This is done by ensuring that the selected exemplars forms a positive definite Gram matrix which is checked by exploiting its Cholesky factorization in an incremental manner. FES is a deterministic rank revealing algorithm delivering a tighter matrix approximation bound. Further, FES can also be used to exactly represent low rank matrices and signals sampled from a unions of independent subspaces. Experimental results show that FES performs comparable to existing methods for tasks such as matrix approximation, feature selection, outlier detection, and clustering.
One of the longstanding problems in spectral graph clustering (SGC) is the so-called model order selection problem: automated selection of the correct number of clusters. This is equivalent to the problem of finding t...
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ISBN:
(纸本)9781509041183
One of the longstanding problems in spectral graph clustering (SGC) is the so-called model order selection problem: automated selection of the correct number of clusters. This is equivalent to the problem of finding the number of connected components or communities in an undirected graph. In this paper, we propose AMOS, an automated model order selection algorithm for SGC. Based on a recent analysis of clustering reliability for SGC under the random interconnection model, AMOS works by incrementally increasing the number of clusters, estimating the quality of identified clusters, and providing a series of clustering reliability tests. Consequently, AMOS outputs clusters of minimal model order with statistical clustering reliability guarantees. Comparing to three other automated graph clustering methods on real-world datasets, AMOS shows superior performance in terms of multiple external and internal clustering metrics.
Internet of Things (IoT) promises to be a key enabler in Smart Manufacturing and Smart Supply Chain. The IoT systems are responsible for enabling and improving the operational efficiencies of factories, plant floors, ...
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ISBN:
(纸本)9781467396233
Internet of Things (IoT) promises to be a key enabler in Smart Manufacturing and Smart Supply Chain. The IoT systems are responsible for enabling and improving the operational efficiencies of factories, plant floors, including assembly plants. These systems are characterized by reliable sensing and reporting of multiple parameters within the factory floor. Such sensing activities offer safe, efficient and optimized performance of not only the machines manufacturing the products, but also the workforce operating them. Industrial IoT (IIoT) systems could suffer from high and uneven energy consumption due to the nature of the network deployment. Such behavior is unacceptable as it not only increases the carbon footprint of the plant, but also makes the planned maintenance of IoT devices for battery replacement a huge challenge. In this paper, we propose a heuristic and opportunistic link selection algorithm, HOLA, which not only reduces the overall energy consumption of the IoT network but also balances it across the network. HOLA achieves this energy-efficiency by opportunistically offloading the IoT device data to smart-devices being carried by the workforce in the factory settings. Further, these smart-devices with multiple radio links such as Bluetooth, Wi-Fi, and 3G/4G LTE heuristically determine the best link to transmit the data to the Cloud based on the quality and energy cost of the link. Our experimental and simulation studies validate that HOLA can improve the energy efficiency of IIoT systems by reducing the overall energy consumption and balancing it across the network.
A Hierarchical Torus Network (HTN) is a 2D-torus network of multiple basic modules, in which the basic modules are 3D-torus networks that are hierarchically interconnected for higher-level networks. The combination of...
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ISBN:
(纸本)9781467366762
A Hierarchical Torus Network (HTN) is a 2D-torus network of multiple basic modules, in which the basic modules are 3D-torus networks that are hierarchically interconnected for higher-level networks. The combination of link selection and channel selection (LS+CS) algorithm improves the dynamic communication performance of the HTN by efficient use of physical links and virtual channels. In this paper, we have evaluated the dynamic communication performances of an HTN is evaluated by using dimension-order routing and LS+CS algorithm under butterfly traffic pattern. It is found that the dynamic communication performance of an HTN using the LS+CS algorithm is better than when the dimension-order routing is used.
Heterogeneous architectures require custom intellectual property (IP) blocks, named 'accelerators', that perform an operation efficiently. Residue Number System (RNS), a non binary compatible arithmetic system...
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ISBN:
(纸本)9781479919994
Heterogeneous architectures require custom intellectual property (IP) blocks, named 'accelerators', that perform an operation efficiently. Residue Number System (RNS), a non binary compatible arithmetic system, can be used in such accelerators. One fundamental challenge in the design of RNS circuits is the selection of the moduli set. Here, we present our algorithm that results in very good moduli set for the given requirements. Experimental results and comparisons with similar algorithms, prove the efficiency of it. The algorithm has been implemented into a public web tool and is available via a web browser.
Mobile Edge Computing (MEC) is an emerging technology, where App vendors are allowed to cache multiple data replicas on geographically distributed edge servers to serve adjacent mobile subscribers. However, this benef...
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Mobile Edge Computing (MEC) is an emerging technology, where App vendors are allowed to cache multiple data replicas on geographically distributed edge servers to serve adjacent mobile subscribers. However, this benefit introduces an extra workload for edge servers and App vendors, as they must audit the integrity of multiple data replicas periodically considering various threats caused by distributed and dynamic MEC environments. The large-scale growth of data replicas certainly is a challenge to design more efficient Edge Data Integrity (EDI) verification approaches. Existing solutions are mostly limited to improving efficiency by optimizing proof generation and verification methods, while the improvement is still far from satisfactory due to adopting indiscriminate inspection philosophy (checking all data replicas without discrimination). In this paper, we make the first attempt to abstract a pre-processing phase and correspondingly study the Unreliable data Replica selection (URS) problem. It can be seamlessly integrated into existing EDI solutions by solving the URS problem at the start of each verification round. Such pre-selection can significantly enhance overall EDI verification efficiency by incorporating the cache service Quality of Service (QoS) and verification success rate, especially in scenarios with a large number of data replicas. Specifically, we first formalize the URS problem as a constrained optimization problem, and further prove its NP -hardness. To address the problem efficiently, we transform it into an easy-to-handle form and develop a Priority-based approach named URS-P. Both theoretical analysis and experimental evaluation validate the effectiveness and efficiency of our proposed solution.
Developing cislunar architectures involves the consideration of many components, and evaluating these architectures requires the consideration of many varied perspectives. The process for making space exploration deci...
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ISBN:
(数字)9781624107115
ISBN:
(纸本)9781624107115
Developing cislunar architectures involves the consideration of many components, and evaluating these architectures requires the consideration of many varied perspectives. The process for making space exploration decisions has become increasingly complicated as interactions amongst participants have become both more impactful and more fraught. There are many additional considerations when conducting this type of analysis, including the context in which the architecture would be operating or the impact of the many assumptions that need to be made. One way to begin to tackle decision-making processes for cislunar architectures is through the development of a tabletop exercise that allows users to see how choices impact the resultant campaign scheduling in real-time, rather than the typical timelines of weeks to months for additional analysis. A tabletop environment brings stakeholder prioritization and interaction to schedule optimization, and contextualizes the decision-making through the use of scenarios. This tabletop tool enables users to compare architectures more quickly than through traditional methods, which could lead to more interactive studies, where different stakeholders are able to participate since new analyses can be run in real-time, or the exploration of more unconventional architectures since there is not the same level of investment needed to obtain results.
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