Obtaining a linearizing feedback and a coordinate transformation map is very difficult, even though the system is feedback linearizable. It is known that finding a desired transformation map and feedback is equivalent to finding an integrating factor for an annihilating one-form for single input nonlinear systems. It is also known that such an integrating factor can be approximated using the simple C.I.R method and tensor product splines. In this paper, it is shown that m integrating factors can always be approximated whenever a nonlinear system with m inputs is feedback linearizable. Next, m zero-forms can be constructed by utilizing these m integrating factors and the same methodology in the single input case. Hence, the coordinate transformation map is obtained.

A reliable antifuse scheme has been very hard to build, which has precluded its implementation in DRAM products. We devised a very reliable multi-cell structure to cope with the large process variation in the DRAM-cell-capacitor type antifuse system. The programming current did not rise above 564 µA even in the nine-cell case. The cumulative distribution of the successful rupture in the multi-cell structure could be curtailed dramatically to less than 15% of the single-cell's case and the recovery problem of programmed cells after the thermal stress (300) had disappeared. In addition, we also presented a Post-Package Repair (PPR) scheme that could be directly coupled to the external high-voltage power rail via an additional pin with small protection circuits, saving the chip area otherwise consumed by the internal pump circuitry. A 1 Gbit DDR SDRAM was fabricated using Samsung's advanced 50 nm DRAM technology, successfully proving the feasibility of the proposed antifuse system implemented in it.

As a result of the growth of sensor-enabled mobile devices, in recent years, users can utilize diverse digital contents everywhere and anytime. However, the interfaces of mobile applications are often unnatural due to limited computational capability, miniaturized input/output controls, and so on. To complement the poor user interface (UI) and fully utilize mobility as feature of mobile devices, we explore possibilities for a new UI of mobile devices. This paper describes the method for recognizing and analyzing a user's continuous action including the user's various gestures and postures. The application example we created is mobile game called AM-Fishing game on mobile devices that employ the accelerometer as the main interaction modality. The demonstration shows the evaluation for the system usability.

Crystallization of amorphous silicon on oxide semiconductors using rapid-thermal annealing in vacuum is investigated. A 30 nm n-type amorphous silicon (a-Si) is deposited on zinc-oxide (ZnO) and aluminum doped zinc-oxide (ZnO:Al) by PECVD on glass substrate. Rapid-thermal annealing for 30 min to 180 min of a-Si on ZnO and ZnO:Al were performed at 600. It is found that crystallization of a-Si on oxide semiconductors can be done in shorter time than that of standard solid-phase crystallization (SPC) of amorphous silicon on glass substrate at 600. It has been verified using Raman spectroscopy that a-Si on ZnO:Al changes into polycrystalline silicon (poly-Si) in 30 min at 600.

It is very difficult to obtain a linearizing feedback and a coordinate transformation map, even though the system is feedback linearizable. It is known that finding a desired transformation map and feedback is equivalent to finding an integrating factor for an annihilating one-form. In this paper we develop a numerical algorithm for an integrating factor involving a set of partial differential equations and corresponding zero-form using the C.I.R method. We employ a tensor product splines as an interpolation method to data which are resulted from the numerical algorithm in order to obtain an approximate integrating factor and a zero-form in closed forms. Next, we obtain a coordinate transformation map using the approximate integrating factor and zero-form. Finally, we construct a stabilizing controller based on a linearized system with the approximate coordinate transformation.

Gains of a roll force AGC (Automatic Gain Controller) have been calculated at the first locked-on-time by FSU (Finishing-mill Set-Up model) in hot strip mills and usually these values are not adjusted during the operating time. Consequently, this conventional scheme cannot cope with the continuous variation of system parameters and circumstance, though the gains can be changed manually with the aid of experts to prevent a serious situation such as inferior mass production. Hence, partially uncontrolled variation still remains on delivery thickness. This paper discusses an effective online algorithm which can adjust the gains of the existing control system by considering the effect of time varying variables. This algorithm improves the performance of the system without additional cost and guarantees the stability of the conventional system. Specifically, this paper reveals the major factors that cause the variation of strip and explores the relationship between AGC gains and the effects of those factors through the analysis of thickness signal which occupy different frequency bands. The proposed tuning algorithm is based on the above relationship and realized through ANFIS (Adaptive-Neuro-based Fuzzy Interface System) which is a very useful method because its fuzzy logics reflect the experiences of professionals about the uncertainty and the nonlinearity of the system. The effectiveness of the algorithm is shown by several simulations which are carried out by using the field data of POSCO corporation (South Korea).

We propose a motor speed ripple elimination method using a state dependent disturbance observer (SDDOB). The SDDOB eliminates the state dependent disturbance in the system regardless of the operation frequency, input time delay and output time delay. The SDDOB and a main proportional integral (PI) controller constitute a robust motor speed controller. Experimental results show the effectiveness of the proposed method.

A method for encoding detection and bit rate classification of AMR-coded speech is proposed. For each texture frame, 184 features consisting of the short-term and long-term temporal statistics of speech parameters are extracted, which can effectively measure the amount of distortion due to AMR. The deep neural network then classifies the bit rate of speech after analyzing the extracted features. It is confirmed that the proposed features provide better performance than the conventional spectral features designed for bit rate classification of coded audio.

The main objective of vehicle suspensions is to improve ride comfort and road holding ability. Though passive suspensions consist of spring and damper, active suspensions adopt an actuator in addition to passive suspensions. In this paper, a quarter car model with an asymmetric hydraulic actuator is used. Moreover, the damping coefficient of the damper, which is changed according to the actuator velocity, is considered. The LPV (Linear Parameter Varying) model is obtained by applying feedback linearization technique. Next, a gain-scheduled controller, based on LQ regulator with different weighting factor, is designed according to the actuator velocity and the stability of the proposed controller is also proved. The effectiveness of the proposed controller is shown by numerical simulations.