Abstract: The present invention discloses a method and device for formulating a coordinated action strategy of SSTS and DVR for voltage sag mitigation. The influence of voltage sag on a whole industrial process of a sensitive user is analyzed, and the sensitive loads of SSTS and DVR which satisfy a governance need are grouped; a practical governance scenario of installing a plurality of DVR is considered to install a minimum-capacity DVR to realize a target of a minimum interruption probability of the whole industrial process of the user; an optimal coordinated governance solution of SSTS and DVR based on sensitive load grouping is proposed; a classification result is obtained for duration time at a time when a voltage sag event occurs through a decision tree constructed based on historical data.

Abstract: In certain aspects, a three-dimensional (3D) memory device includes a first semiconductor structure, a second semiconductor structure, and a bonding interface between the first semiconductor structure and the second semiconductor structure. The first semiconductor structure includes an array of memory cells, a first peripheral circuit of the array of memory cells, and a polysilicon layer between the array of memory cells and the first peripheral circuit. The first peripheral circuit includes a first transistor. The second semiconductor structure includes a second peripheral circuit of the array of memory cells. The second peripheral circuit includes a second transistor.

Abstract: In certain aspects, a three-dimensional (3D) memory device includes a first semiconductor structure, a second semiconductor structure, a third semiconductor structure, and a first bonding interface between the first semiconductor structure and the second semiconductor structure. The first semiconductor structure includes an array of memory cells. The second semiconductor structure includes a first peripheral circuit of the array of memory cells. The first peripheral circuit includes a first transistor. A third semiconductor structure includes a second peripheral circuit of the array of memory cells. The second peripheral circuit includes a second transistor. The first semiconductor structure, the second semiconductor structure, and the third semiconductor structure are stacked over one another.

Abstract: An authentication method comprising creating electrocardiogram data of users; calculating a similarity between electrocardiogram data of each user and template data created by averaging electrocardiogram data of each user; creating and training a first NNmodel for every user by using similarities between electrocardiogram data of a user and template data of the same user and similarities between electrocardiogram data of a user and template data of another user, and creating and training second NNmodels for users by using similarities between electrocardiogram data of a user and template data of the user and similarities between electrocardiogram data of the user and template data of another user; and executing a first step in which the similarities calculated using electrocardiogram data for authentication of a user to be authenticated and template data are input to the first NNmodel, and executing a second step in which the similarities are input to the second NNmodels.

Abstract: An authentication method comprising creating electrocardiogram data of users; calculating a similarity between electrocardiogram data of each user and template data created by averaging electrocardiogram data of each user; creating and training a first NNmodel for every user by using similarities between electrocardiogram data of a user and template data of the same user and similarities between electrocardiogram data of a user and template data of another user, and creating and training second NNmodels for users by using similarities between electrocardiogram data of a user and template data of the user and similarities between electrocardiogram data of the user and template data of another user; and executing a first step in which the similarities calculated using electrocardiogram data for authentication of a user to be authenticated and template data are input to the first NNmodel, and executing a second step in which the similarities are input to the second NNmodels.

Abstract: A pacing-pulse detecting circuit 3 detects pacing pulses from an electrocardiogram signal led from an electrocardiogram electrode 1. A mode-status judging means 21 judges a mode status, a pacing mode or a nonpacing mode, on the basis of the pacing pulse detected. The detect result is transmitted to a CPU 5. The CPU 5 causes a display device 10 to display the result. An operator sees the display and operates a key 22, and gives an instruction to start a blood pressure measurement to the CPU 5. The CPU 5 drives a pump 13 and an exhaust valve 14 to supply and discharge air to and from a cuff 11, and measures a blood pressure by use of pressure data led from a pressure sensor 15.

Abstract: An apparatus for non-invasion heart monitoring includes electrocardiogram measuring means (1) for measuring electrocardiograms, pulse wave measuring means (2) for measuring pulse waves, and a CPU (30) for processing electrocardiogram signals derived from the electrocardiogram measuring means (1) and pulse wave signals derived from the pulse-wave measuring means (2). The CPU (30) detects the amplitudes of the pulse waves corresponding to the R waves of the cardiogram and the pulse wave propagation times, and computes a ratio (Nr/N) of the heart rate N and the heart rate Nr exclusive of the heart beats of wave deficits.

Abstract: A pacing-pulse detecting circuit 3 detects pacing pulses from an electrocardiogram signal led from an electrocardiogram electrode 1. A mode-status judging means 21 judges a mode status, a pacing mode or a nonpacing mode, on the basis of the pacing pulse detected. The detect result is transmitted to a CPU 5. The CPU 5 causes a display device 10 to display the result. An operator sees the display and operates a key 22, and gives an instruction to start a blood pressure measurement to the CPU 5. The CPU 5 drives a pump 13 and an exhaust valve 14 to supply and discharge air to and from a cuff 11, and measures a blood pressure by use of pressure data led from a pressure sensor 15.

Abstract: A pacing-pulse detecting circuit 3 detects pacing pulses from an electrocardiogram signal led from an electrocardiogram electrode 1. A mode-status judging means 21 judges a mode status, a pacing mode or a nonpacing mode, on the basis of the pacing pulse detected. The detect result is transmitted to a CPU 5. The CPU causes a display device 10 to display the result. An operator sees the display and operates a key 22, and gives an instruction to start a blood pressure measurement to the CPU 5. The CPU 5 drives a pump 13 and an exhaust valve 14 to supply and discharge air to and from a cuff 11, and measures a blood pressure by use of pressure data led from a pressure sensor 15.

Abstract: An electrocardiogram signal derived from electrocardiogram measuring means 1 and a pulse signal derived from pulse-wave measuring means 2 are applied to a CPU 30. The CPU 30 processes the cardiogram signal to detect a QRS wave signal, and processes the pulse signal to detect the amplitude of the pulse signal. The CPU 30 judges whether or not the QRS wave is caused by a ventricular premature contraction. If two QRS waves, not caused by ventricular premature contraction, occurs successively, and the CPU 30 judges if A0.times.k>A1. The CPU 30 judges that a supraventricular extrasystole is occurred. Here, A0 is an amplitude of the first QSR wave; A1 is an amplitude of the second QSR wave; and k is a preset value, 0<k<1.

Abstract: After an initial blood pressure measurement using a cuff 2 has been made, not only a pulse wave propagation time Tt is counted consecutively, but also a pulse wave propagation time change .DELTA.T is calculated every time the pulse wave propagation time Tt is counted and compared with a pulse wave propagation change threshold .DELTA.Ts. When the pulse wave propagation time change .DELTA.T exceeds the pulse wave propagation time change threshold .DELTA.Ts, not only a blood pressure value BPt is measured with the cuff 2, but also a pulse wave propagation time Tt.sub.1 is counted. If there are at least two sets of data, each set of data consisting of a blood pressure value BPt and a pulse wave propagation time Tt.sub.1, coefficients .alpha., .beta. specific to a subject are calculated from such two sets of data by a least-squares method. Then, the pulse wave propagation time change threshold .DELTA.Ts is calculated from the coefficient .alpha., and the current pulse wave propagation time change threshold .DELTA.