This paper presents the results of an extensive research study to develop a national model for an undergraduate curriculum in Industrial Engineering. A departmental reform strategy was developed and applied to reengin...
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Home service robots increasingly need to provide diverse and complex services such as cooking, sweeping and dishwashing. These services inevitably require a number of software functions simultaneously. For example, th...
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Home service robots increasingly need to provide diverse and complex services such as cooking, sweeping and dishwashing. These services inevitably require a number of software functions simultaneously. For example, the cooking service requires an arm manipulation function to grasp dishes, an navigation function to move around, an object recognition function to find foods, an speech recognition function to understand user requirements, and etc. However, when the services and software functions are executed simultaneously in a robot without run-time software management, those may cause malfunction due to resource contention. In this paper, we describe the situation that causes resource contention and formulate architecture-based adaptation in robot software systems. Based on the formulation we proposed an approach to dynamic robot software management that effectively uses robot computing resources.
With myriad information being generated from high-throughput experiments such as microarrays and sequencing technologies, an ever-increasing amount of data is being recorded and analyzed with the help of hierarchical ...
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ISBN:
(纸本)9780615153148
With myriad information being generated from high-throughput experiments such as microarrays and sequencing technologies, an ever-increasing amount of data is being recorded and analyzed with the help of hierarchical ontologies, such as the Gene Ontology (GO). We have developed a novel framework-based on the well established foundations of information theory - that allows for the evaluation of new types of hypotheses. The framework, encapsulated in Open Biomedical Ontology-Based Exploration and Search (OBOES), has already been applied in the investigation of different kinds of questions. The resulting framework enables the new field of information theoretic ontology-based analysis. We have applied this framework to create methods to re-engineer ontologies, explore fundamental questions on the evolution of biological complexity, determine optimal ontology terms for bioinformatics analysis, and quantify the usefulness of biofluids as proxies for tissues/diseases. In each case, we found that our methods provide novel, significant findings. An open source Java implementation of OBOES is available at: http://***. net.
Mobile Learning makes students get the advantages of both traditional learning and e-learning. How to give students learning sequence suggestions in the mobile learning environment is a big issue and is also the goal ...
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Mobile Learning makes students get the advantages of both traditional learning and e-learning. How to give students learning sequence suggestions in the mobile learning environment is a big issue and is also the goal of this paper. This research uses knowledge map to store the characteristics of each learning object and designs a situated map to represent spatial knowledge in the mobile learning environment. By using these two knowledge structures, knowledge map and situated map, the system created by this research can generate various navigation sentences and ask students to observe the characteristics of learning objects. This research also takes information theory into consideration in order to decide which navigation sentence should deliver to the student first. The system calculates the entropy for each generated sentence and finds the most appropriate one to deliver to the student. At the end of this paper, an experiment system is implemented for the 5th year biology course, Plant Observation.
Recent work in blind source separation applied to anechoic mixtures of speech allows for improved reconstruction of sources that rarely overlap in a time-frequency representation. While the assumption that speech mixt...
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In this paper, we try to estimate Japan's cabinet approval ratings by using neural networks. In addition, we try to extract the important features in input patterns. This is the first attempt to use neural network...
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ISBN:
(纸本)9780889866317
In this paper, we try to estimate Japan's cabinet approval ratings by using neural networks. In addition, we try to extract the important features in input patterns. This is the first attempt to use neural networks and to interpret the mechanism of inference for approval estimation in a comprehensive way. Experimental results show that neural networks have much better performance than that obtained by the standard regression analysis in terms of training and testing errors. The information loss analysis reveals that the first variable, that is, the previous ratings should play the most important role in inference. Though the experimental result here shown is a preliminary one, it certainly suggests a possibility of the automatic inference of cabinet approval ratings.
We describe complementary iconic and symbolic representations for parsing the visual world. The iconic pixmap representation is operated on by an extensible set of "visual routines" (Ullman, 1984;Forbus et a...
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With the human genome sequenced, attention has been shifting to proteins and their function. Several technologies including mass spectrometry and gel electrophoresis have traditionally been used to study proteins. The...
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High-throughput microarrays inform us on different outlooks of the molecular mechanisms underlying the function of cells and organisms. While computational analysis for the microarrays show good performance, it is sti...
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High-throughput microarrays inform us on different outlooks of the molecular mechanisms underlying the function of cells and organisms. While computational analysis for the microarrays show good performance, it is still difficult to infer modules of multiple co-regulated genes. Here, we present a novel classification method to identify the gene modules associated with cancers from microarray data. The proposed approach is based on 'hypernetworks', a hypergraph model consisting of vertices and weighted hyperedges. The hypernetwork model is inspired by biological networks and its learning process is suitable for identifying interacting gene modules. Applied to the analysis of microRNA (miRNA) expression profiles on multiple human cancers, the hypernetwork classifiers identified cancer-related miRNA modules. The results show that our method performs better than decision trees and naive Bayes. The biological meaning of the discovered miRNA modules has been examined by literature search.
This paper provides an overview of quantitative and qualitative outcome of the national program for e-learning in Taiwan (ELNP for short). The national program was planned and initiated in 2002 by the National science...
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This paper provides an overview of quantitative and qualitative outcome of the national program for e-learning in Taiwan (ELNP for short). The national program was planned and initiated in 2002 by the National science Council. Taiwan government wished to promote e-learning industry and make all people have same opportunity to learn knowledge via e-learning. A five-year national program for e-learning started from 2003. This paper shows both of quantitative and qualitative outcomes of national program in the past four years from four different ways: public welfare, academic researching output, e-learning industry, technological results.
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