Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant an...
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Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F 1 and Accuracy have been chosen as the key evaluation measures. We stress the F 1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F 1 and Accuracy compared with three other influential baseline models.
A simulation of BB84 protocol of QKD using photonic simulator Optisystem is demonstrated. The simulation is divided into two categories which are without security attacks scenario and with several attacks scenario tha...
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A simulation of BB84 protocol of QKD using photonic simulator Optisystem is demonstrated. The simulation is divided into two categories which are without security attacks scenario and with several attacks scenario that consists of Intercept and Resend and sent new qubits. The simulation results meet the theory of BB84. This project is able to provide better understanding about the quantum key distribution process especially in BB84 protocol.
This paper presents a novel segmentation method for isointense signal tumor appeared in T1-weighted or T2-weighted magnetic resonance (MR) images. The proposed method improves the well-known Grow-cut algorithm using t...
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ISBN:
(纸本)9781479958238
This paper presents a novel segmentation method for isointense signal tumor appeared in T1-weighted or T2-weighted magnetic resonance (MR) images. The proposed method improves the well-known Grow-cut algorithm using the improved local transition rule. It applied the level set theory to extract tumor from the background by using strength probability surface map by threshold value. Heaviside step function are applied to assign the boundary among seed and background. For performance evaluation, tumor datasets on isointense signal with T1-weighted MRI acquired from Kitware/MIDAS repository are experimented throughout. The well-known grow-cut and tumor-cut algorithms are compared using dice similarity coefficient (DSC). In this regard, the proposed method provides the better results by reporting DSC of 84.17%higher than Grow-cut and Tumor-cutwith 80.81% and 80.14%, respectively.
A handshake is an embodied interaction for displaying closeness through physical contact. In this study, we develop a handshake response motion model for a handshake during active approach to a human on the basis of a...
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A handshake is an embodied interaction for displaying closeness through physical contact. In this study, we develop a handshake response motion model for a handshake during active approach to a human on the basis of analysis of handshake motions between humans. We also develop a handshake robot system that uses the proposed model. A sensory evaluation is performed for analyzing the time lag preferred by humans between the approaching motion and the hand motion generated by the robot system. Another sensory evaluation is performed for determining the preferred timing of a handshake motion that is accompanied by a voice greeting. The evaluation results demonstrate that the proposed model can generate a handshake response motion during active approach that is preferred by humans. Furthermore, the effectiveness of the proposed model is demonstrated.
An on-chip environment monitor that can estimate a chip temperature and a power supply voltage has been developed to assist accurate circuit delay measurement by field test. The monitor consists of digital circuits an...
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An on-chip environment monitor that can estimate a chip temperature and a power supply voltage has been developed to assist accurate circuit delay measurement by field test. The monitor consists of digital circuits and satisfies several features desired for the field test. This paper describes the architecture of the monitor and how to estimate the temperature and voltage in field, and finally shows simulation and TEG results on estimation accuracy.
The aim of this study is to increase the friction coefficient between.C/C composites at low temperature to moderate the dependence of the frictional coefficient on the temperature condition.
The aim of this study is to increase the friction coefficient between.C/C composites at low temperature to moderate the dependence of the frictional coefficient on the temperature condition.
A design of cyber physical system is one of the promising domains, where the market of data is expected to penetrate. However, there are risks that any design hypotheses might be supported with data sets in the market...
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A design of cyber physical system is one of the promising domains, where the market of data is expected to penetrate. However, there are risks that any design hypotheses might be supported with data sets in the market, when engineers focus on a particular part of the data intentionally or accidentally. Because, the data sets, especially big data, include diverse kinds of variables to mislead reasoning of the design hypotheses. The validity could not be estimated by the data themselves but could be confirmed only by robustness of the logic behind the design argumentation. In this paper, we propose a system design method with data sets in the market and apply the proposed method to design process for a diagnosis system for semiconductor equipment.
This paper describes the development of an embedded smart home management scheme over the Ethernet network. The platform of the smart home management system is built using bespoke embedded system design. An embedded c...
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This paper describes the development of an embedded smart home management scheme over the Ethernet network. The platform of the smart home management system is built using bespoke embedded system design. An embedded control module developed by exploiting the Web Services mechanism, consist of 15 monitoring channels based on XML SOAP standards. Each channel is integrated to dedicated smart home management scheme and performs bi-directional real-time control. In the event of server unavailability, a mobile based communication module using GSM has been deployed as an alternate management mechanism. The proposed embedded-enabled solution offers bi-directional real-time management as well as optimized performance for smart home environment.
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