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The lack of real-time tools capable of detecting risk of blackouts is one of the contribution factors to the recent large blackouts occurred around the world. In terms of dynamic security assessment (DSA), artificial intelligence and data mining techniques have been widely applied to facilitate very fast DSA for enhanced situational awareness of insecurity. However, many of the current state-of-the-art...
Modern automotive engines are controlled by the electronic control unit (ECU). The engine performance referred to as output torque is significantly affected by the setup of control parameters in the ECU. Traditional ECU tune-up is done by trial-and-error method through repeated dynamometer tests. LS-SVM (Least Squares Support Vector Machines) is a powerful machine learning technique which can handle...
A new blind source extraction method in widespread noise conditions is proposed, which is based on multiple frequency-domain independent component analysis (FDICA) combining projection back and spectral subtraction. In addition, We implement the proposed method to digital signal processor (DSP) for a more realistic real-time operation, and develop a new blind source extraction (BSE) microphone which...
In the advanced Low Power (LP) CMOS technology nodes gate-to-source/drain overlap capacitance (COV), gate-to-contact capacitance (CCO) and gate sidewall fringe capacitance (Cf) have become increasingly important component(s) of transistor parasitic. Accurate extraction and modeling of these parasitic are essential in accurate estimation of circuit performance. In this paper we describe test structure...
In this paper, we propose an accurate full 3D EM behavioral model of PD chips for the first time. The model, which is meshed at 130 GHz, runs for about 17 minutes on an Intel Core2 Duo CPU@3 GHz PC with 3.5 GB of RAM. The impact of various parameters in wire- bonding transitions for transmission characteristic is summarized in the Table I. When numbers of bonding wires are placed separately all through...
Increasingly large text damsels and the high dimensionality associated with natural language create a great challenge in text mining, In this research, a systematic study is conducted. in which three different document representation methods for text are used, together with three Dimension Reduction Techniques (DRT), in the context of the text clustering problem. Several standard benchmark datasets...
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