For the conventional single-ended eFuse cell, sensing failures can occur due to a variation of a post-program eFuse resistance during the data retention time and a relatively high program resistance of several kilo oh...For the conventional single-ended eFuse cell, sensing failures can occur due to a variation of a post-program eFuse resistance during the data retention time and a relatively high program resistance of several kilo ohms. A differential paired eFuse cell is designed which is about half the size smaller in sensing resistance of a programmed eFuse link than the conventional single-ended eFuse cell. Also, a sensing circuit of sense amplifier is proposed, based on D flip-flop structure to implement a simple sensing circuit. Furthermore, a sensing margin test circuit is proposed with variable pull-up loads out of consideration for resistance variation of a programmed eFuse. When an 8 bit eFuse OTP IP is designed with 0.18 ~tm standard CMOS logic of TSMC, the layout dimensions are 229.04 μm ×100.15μm. All the chips function successfully when 20 test chips are tested with a program voltage of 4.2 V.展开更多
In this paper we discuss Newtonian Mechanics on Kahler Manifold, and also givefoe complex mathematical aspects of Newton's law, the law of kinetic energy, the lawof kinetic quantity,the equation of motion and the ...In this paper we discuss Newtonian Mechanics on Kahler Manifold, and also givefoe complex mathematical aspects of Newton's law, the law of kinetic energy, the lawof kinetic quantity,the equation of motion and the 'general equation of dynamics',and so on.展开更多
There have been many skewed cancer gene expression datasets in the post-genomic era.Extraction of differential expression genes or construction of decision rules using these skewed datasets by traditional algorithms w...There have been many skewed cancer gene expression datasets in the post-genomic era.Extraction of differential expression genes or construction of decision rules using these skewed datasets by traditional algorithms will seriously underestimate the performance of the minority class,leading to inaccurate diagnosis in clinical trails.This paper presents a skewed gene selection algorithm that introduces a weighted metric into the gene selection procedure.The extracted genes are paired as decision rules to distinguish both classes,with these decision rules then integrated into an ensemble learning framework by majority voting to recognize test examples;thus avoiding tedious data normalization and classifier construction.The mining and integrating of a few reliable decision rules gave higher or at least comparable classification performance than many traditional class imbalance learning algorithms on four benchmark imbalanced cancer gene expression datasets.展开更多
文摘For the conventional single-ended eFuse cell, sensing failures can occur due to a variation of a post-program eFuse resistance during the data retention time and a relatively high program resistance of several kilo ohms. A differential paired eFuse cell is designed which is about half the size smaller in sensing resistance of a programmed eFuse link than the conventional single-ended eFuse cell. Also, a sensing circuit of sense amplifier is proposed, based on D flip-flop structure to implement a simple sensing circuit. Furthermore, a sensing margin test circuit is proposed with variable pull-up loads out of consideration for resistance variation of a programmed eFuse. When an 8 bit eFuse OTP IP is designed with 0.18 ~tm standard CMOS logic of TSMC, the layout dimensions are 229.04 μm ×100.15μm. All the chips function successfully when 20 test chips are tested with a program voltage of 4.2 V.
文摘In this paper we discuss Newtonian Mechanics on Kahler Manifold, and also givefoe complex mathematical aspects of Newton's law, the law of kinetic energy, the lawof kinetic quantity,the equation of motion and the 'general equation of dynamics',and so on.
基金Supported by the National Natural Science Foundation of China(No.61105057)the Ph.D Foundation of Jiangsu University of Science and Technology(Nos.35301002 and 35211104)
文摘There have been many skewed cancer gene expression datasets in the post-genomic era.Extraction of differential expression genes or construction of decision rules using these skewed datasets by traditional algorithms will seriously underestimate the performance of the minority class,leading to inaccurate diagnosis in clinical trails.This paper presents a skewed gene selection algorithm that introduces a weighted metric into the gene selection procedure.The extracted genes are paired as decision rules to distinguish both classes,with these decision rules then integrated into an ensemble learning framework by majority voting to recognize test examples;thus avoiding tedious data normalization and classifier construction.The mining and integrating of a few reliable decision rules gave higher or at least comparable classification performance than many traditional class imbalance learning algorithms on four benchmark imbalanced cancer gene expression datasets.
