An algorithm for time division multiple access (TDMA) is found to be applicable in converting existing distributed algorithms into a model that is consistent with sensor networks. Such a TDMA service needs to be self-...
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This paper assesses and analyzes a harmonic vector modeling method for reducing disturbance torque and motion state estimation error using quantized input measurements of position. There is a finite resolution availab...
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This paper assesses and analyzes a harmonic vector modeling method for reducing disturbance torque and motion state estimation error using quantized input measurements of position. There is a finite resolution available for any digital interface and quantization will always be present in some form. Although not possible to completely reconstruct a quantized measured state, it is possible to attenuate deterministic quantization characteristics. The discussed method models quantized position feedback as a spatially rotating vector consisting of fundamental and harmonic components. The error mitigation strategy involves decoupling these spatial quantization harmonics from the actual fundamental position, using heterodyning tracking observer topologies
Long-duration surface missions to the Moon and Mars will require bases to accommodate habitats for the astronauts, as well as indoor laboratory facilities, in-situ resource plants, power plants, and scientific/surface...
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ISBN:
(纸本)0784408300
Long-duration surface missions to the Moon and Mars will require bases to accommodate habitats for the astronauts, as well as indoor laboratory facilities, in-situ resource plants, power plants, and scientific/surface mobility equipment. Transporting the materials and equipment required to build the necessary habitats would be costly and difficult. However, the use of planetary resources to produce construction materials, or even as naturally found (such as lunar regolith utilized as an outer layer for radiation shielding, or regolith in bags as wall structure), could drastically reduce the upmass for habitats. The materials chosen for the habitat walls play a direct role in protection against each of the mentioned hazards. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. For example a 3-layer habitat wall created from 20 possible materials all with varying thicknesses would have #number of layers(possible material types)∧(possible thicknesses) = 320∧inf possible solutions. Clearly, an optimization method is warranted for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces. To overcome the large search regions, a habitat wall design tool using genetic algorithms has been developed. GAs use a "survival of the fittest" philosophy, where the most fit individuals are more likely to survive and reproduce, therefore transmitting their genes to the next generation. This paper focuses on finding optimal GA parameters for the habitat optimization tool. This tool is a multiobjective formulation of structural analysis, heat loss, radiation, and meteoroid protection. Some of the constraint calculations (i.e. safety factor, deflection, and heat loss) require long computation times. Even though each material has a designated thickness range, the number of different values within that range is near infinite;therefore, the searc
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which assume a relatively balanced class distri...
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Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which assume a relatively balanced class distribution and equal misclassification costs. This learning difficulty attracts a lot of research interests. Most efforts concentrate on bi-class problems. However, bi-class is not the only scenario where the class imbalance problem prevails. Reported solutions for bi-class applications are not applicable to multi-class problems. In this paper, we develop a cost-sensitive boosting algorithm to improve the classification performance of imbalanced data involving multiple classes. One barrier of applying the cost-sensitive boosting algorithm to the imbalanced data is that the cost matrix is often unavailable for a problem domain. To solve this problem, we apply Genetic Algorithm to search the optimum cost setup of each class. Empirical tests show that the proposed cost-sensitive boosting algorithm improves the classification performances of imbalanced data sets significantly.
Supply chain management (SCM) environments are often dynamic markets providing a plethora of information, either complete or incomplete. It is, therefore, evident that such environments demand intelligent solutions, w...
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Supply chain management (SCM) environments are often dynamic markets providing a plethora of information, either complete or incomplete. It is, therefore, evident that such environments demand intelligent solutions, which can perceive variations and act in order to achieve maximum revenue. To do so, they must also provide some sophisticated mechanism for exploiting the full potential of the environments they inhabit. Advancing on the way autonomous solutions usually deal with the SCM process, we have built a robust and highly-adaptable mechanism for efficiently dealing with all SCM facets, while at the same time incorporating a module that exploits data mining technology in order to forecast the price of the winning bid in a given order and, thus, adjust its bidding strategy. The paper presents our agent, Mertacor, and focuses on the forecasting mechanism it incorporates, aiming to optimal agent efficiency
Connectors are used to realize component interactions in component systems. Apart from their primary function, which is mediating the communication, their implementation can also support additional features that, whil...
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This study explores the relationship between program slices and faults. The aim is to investigate whether the characteristics of program slices can be used to identify faultprone software components. Slicing metrics a...
In this paper, we present a formal process model to support the comprehension and maintenance of softwaresystems. The model provides a formal ontological representation that supports the use of reasoning services acr...
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ISBN:
(纸本)9783540694885
In this paper, we present a formal process model to support the comprehension and maintenance of softwaresystems. The model provides a formal ontological representation that supports the use of reasoning services across different knowledge resources. In the presented approach, we employ our Description Logic knowledge base to support the maintenance process management, as well as detailed analyses among resources, e.g., the traceability between various software artifacts. The resulting unified process model provides users with active guidance in selecting and utilizing these resources that are context-sensitive to a particular comprehension task. We illustrate both, the technical foundation based on our existing SOUND environment, as well as the general objectives and goals of our process model.
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