Since the first introduction of integrated circuits (ICs), there has been dramatic improvements in semiconductor manufacturing technologies. To minimize even slightest faults in manufacturing processes, many studies a...
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ISBN:
(纸本)9781538679753
Since the first introduction of integrated circuits (ICs), there has been dramatic improvements in semiconductor manufacturing technologies. To minimize even slightest faults in manufacturing processes, many studies are being conducted to systematically analyze the causes of faults. In this paper, we propose an algorithm that finds the causes of faults by clustering the fault detection results. Our experiments show that our algorithm forms good clusters of runs having similar sources of faults.
In the large research area of wireless body area networks, cooperative applications involving several users is attracting strong interests. This cooperation may target a simple information exchange or even some cooper...
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ISBN:
(纸本)9781479937844
In the large research area of wireless body area networks, cooperative applications involving several users is attracting strong interests. This cooperation may target a simple information exchange or even some cooperative decision such as swarm coordination. We consider in this paper such a swarm of users moving in a common direction and we are interested in the mechanisms allowing to propagate and share some common information. We extend and improve a previous algorithm derived as a max-consensus approach. We describe a complete experimental setup deployed during a real bike race with 200 runners. We provide a deep analysis of the radio links properties (stability, strength...) and the equivalent graph evolution (graph diameter, neighborhood characterization...) from the record made on 20 nodes. At the best of our knowledge, this paper is the first one providing such analysis in a real experiment with a swarm of 200 nodes located on bikes during an official race.
Education is a fundamental right that enriches everyone's life. However, physically challenged people often debar from the general and advanced education system. Audio-Visual Automatic Speech Recognition (AV-ASR) ...
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Education is a fundamental right that enriches everyone's life. However, physically challenged people often debar from the general and advanced education system. Audio-Visual Automatic Speech Recognition (AV-ASR) based system is useful to improve the education of physically challenged people by providing hands-free computing. They can communicate to the learning system through AV-ASR. However, it is challenging to trace the lip correctly for visual modality. Thus, this paper addresses the appearance-based visual feature along with the co-occurrence statistical measure for visual speech recognition. Local Binary Pattern-Three Orthogonal Planes (LBP-TOP) and Grey-Level Co-occurrence Matrix (GLCM) is proposed for visual speech information. The experimental results show that the proposed system achieves 76.60 % accuracy for visual speech and 96.00 % accuracy for audio speech recognition.
This paper proposes a control scheme for a kind of complex systems whose dynamics follow statistical law. First, inspired by data mining technology, the samples are clustered into several classes reflecting the workin...
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ISBN:
(纸本)9781728101057
This paper proposes a control scheme for a kind of complex systems whose dynamics follow statistical law. First, inspired by data mining technology, the samples are clustered into several classes reflecting the working pattern by modified ISODATA method. Second, based on the clustering result, the cell state space is constructed within global and local target cells respectively by Cartesian product, and the cell mapping further is created via the analysis of pattern time series. Third, by the reverse searching algorithm, global optimal paths to the target cell are found and the information provided by the searching paths constitute the optimal controller at a coarse-grained level so as to bring the system into the target cell quickly, once enter into the target cell, another controller which consists of the subcell mapping with the optimal cost increment in refined granularity level is applied in order to reduce steady-state error. Finally, a simulation in the dynamic trajectory of a sintering process is given to demonstrate the feasibility of the proposed approach.
In order to prolong the network lifetime, energy-aware protocols should be designed to adapt the characteristic of wireless sensor networks. clustering is a kind of key routing technique used to reduce energy consumpt...
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ISBN:
(纸本)9780769537450
In order to prolong the network lifetime, energy-aware protocols should be designed to adapt the characteristic of wireless sensor networks. clustering is a kind of key routing technique used to reduce energy consumption. In this paper, a new clustering algorithm MNLC (Maximum Network Lifetime clustering algorithm) for energy heterogeneous sensor networks is proposed. The algorithm uses distributed, dynamic clustering process. On the one hand, cluster-head selection is primarily determined by the residual energy level of each node, on the other hand, the ordinary nodes select which cluster to join according to the remaining energy level of the candidate cluster-heads and the parameter of communication cost in a cluster, so as to effectively achieve the balanced distribution of energy loss in the network. Simulation results show that MNLC could better implement load balance and prolong the network lifetime in heterogeneous environments.
In this paper we present an original framework to extract representative groups from a dataset, and we validate it over a novel case study. The framework specifies the application of different clustering algorithms, t...
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ISBN:
(纸本)9781424481262
In this paper we present an original framework to extract representative groups from a dataset, and we validate it over a novel case study. The framework specifies the application of different clustering algorithms, then several statistical and visualisation techniques are used to characterise the results, and core classes are defined by consensus clustering. Classes may be verified using supervised classification algorithms to obtain a set of rules which may be useful for new data points in the future. This framework is validated over a novel set of histone markers for breast cancer patients. From a technical perspective, the resultant classes are well separated and characterised by low, medium and high levels of biological markers. Clinically, the groups appear to distinguish patients with poor overall survival from those with low grading score and better survival. Overall, this framework offers a promising methodology for elucidating core consensus groups from data.
K-means is still a popular clustering algorithm and active research area. The research is majorly focused at improving efficiency and effectiveness of the method. This paper proposes combined approach of a ranked init...
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ISBN:
(纸本)9781509020287
K-means is still a popular clustering algorithm and active research area. The research is majorly focused at improving efficiency and effectiveness of the method. This paper proposes combined approach of a ranked initialization and normalization of data values with k-means. Three variations of a score based initialization approach is proposed. Experiments are performed on normalized data to prove the superiority of the proposed algorithm.
The boom is the key load-bearing component of the crane, and its health seriously threatens the service performance of the crane. In order to ensure the safe production of cranes, nondestructive testing (NDT) and stru...
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ISBN:
(纸本)9783031073229;9783031073212
The boom is the key load-bearing component of the crane, and its health seriously threatens the service performance of the crane. In order to ensure the safe production of cranes, nondestructive testing (NDT) and structural health monitoring (SHM) of boom become more and more urgent and important. In this paper, the intelligent defect location algorithm based on helical guided waves is applied to the weld defect detection of U-shaped boom. Intelligent defect location algorithm is an imaging algorithm that combines ellipse imaging principle, evolutionary algorithm and K-means clustering algorithm. This paper verifies the effectiveness of this algorithm for weld defect location of U-shaped boom through experimental research. Firstly, the propagation regularity of helical guided waves in the U-shaped boom structure is studied. In addition, the elliptical imaging algorithm is used to image and analyze the weld defects in the U-shaped boom, and the location of the defects is preliminarily determined. The defect location analysis of weld defects is carried out by using the intelligent defect location algorithm. By comparing the imaging results of the two methods, it is found that the intelligent defect location algorithm has higher resolution and can effectively improve the defect location accuracy. This algorithm provides a tool for health monitoring of special-shaped structures based on guided waves.
A key task in organization design is to group elements (e.g., roles) into sub-units (e.g., teams or departments). This task is computationally challenging as one must take into consideration a potentially large number...
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A key task in organization design is to group elements (e.g., roles) into sub-units (e.g., teams or departments). This task is computationally challenging as one must take into consideration a potentially large number of interdependencies between the elements. It also requires data about work processes in the organization, which are rarely present. We have initiated a research program that aims at developing a tool-Reconfig-to improve grouping decisions. It first collects data from employees about their working relationships (i.e., interdependencies) and then uses a computer algorithm to cluster the data in the most optimal manner. The clustered solution represents the formal structure that minimizes coordination costs by grouping the most highly interdependent elements together. We describe the tool, report on two pilot applications, and discuss both the future potential and limitations of the approach.
PurposeThis study aims to explore the success factors of tourism performing arts (TPA) programs by analyzing a large data set of online reviews. Design/methodology/approachA total of 195,230 reviews from *** were coll...
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PurposeThis study aims to explore the success factors of tourism performing arts (TPA) programs by analyzing a large data set of online reviews. Design/methodology/approachA total of 195,230 reviews from *** were collected and preprocessed. A deep learning method was leveraged to estimate the similarity between words. Then, regression analysis was conducted to determine success factors. FindingsThis study extracted four positive and two negative factors affecting tourist satisfaction with tourism performance arts. The results demonstrate that the tourists paid the most attention to the traditional Chinese cultural aspects, audiovisual effects and the actors' performing enthusiasm. Research limitations/implicationsDespite this study's large data set, the focused was only on Chinese reviews. It would be useful and interesting to compare the success factors of tourism performance arts programs offered in different countries. Practical implicationsThe study findings can contribute to the development of TPA programs to attract tourists to travel destinations. Originality/valueThis study demonstrates that analyzing online reviews of TPA through text mining technology is an effective method of understanding tourist satisfaction.
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