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In this work, we report sub-ns polarization switching in highly scaled 25 nm ferroelectric (FE) FinFET with Hf 0.5 Zr 0.5 O 2 (HZO) ferroelectric (FE)/SiO 2 dielectric (DE) gate stack for high performance CPU application for the first time. Observed limited endurance was attributed to the increase of trap density in the stack, which was quantitatively analyzed upon program/erase cycles by various methods including newly adopted low-frequency noise (LFN) characteristics for resolving spatial and energetic distribution of traps. In particular, we identified three different types of traps at FE/DE interface (D it_2 ) and SiO 2 /Si channel interface (D it_1 ) as well as in the bulk oxide (N ot ) of the HZO/SiO 2 gate stack of FE FinFETs. In addition, with the developed trap analysis, we investigated radiation-induced degradation of HZO/SiO 2 gate stack for application under harsh environments. Highly scaled and high performance FE FinFETs with enhanced endurance would provide a viable solution for future platform of low-power computing.

The problem of determining the transformation between the end-effector and the camera attached to the robot arm is called hand-eye calibration. For this calibration, the pose of the robot and the image data of the calibrated camera must be acquired. Since industrial robots use fixed focus cameras, the depth of field is limited, and variable focus lenses cannot determine the camera position or pose with high accuracy because the parameters of the camera change. If the pose of a robot is out of depth of field (DOF), the camera is out of focus, and the image is blurred. If hand-eye calibration is performed using these images, the resulting data includes errors. In this paper, image restoration is performed using deep learning on a blurred image where a marker cannot be found because it is out of focus. This technique is used to sharply restore images and demonstrate a technique for finding markers. We improved the precision of the hand-eye calibration problem by obtaining a clear image restored even in various pose of the robot and reducing the error that occurs in the blurred image.

In autonomous driving systems, many approach have been developed based on high-precision sensors, high computing power, development of various networks in academia and industry. The key point of an autonomous car is that it needs to know what is happening in the driving situation and an action corresponding to this situation must be created and operated. In this paper, we propose the system structure and method of a autonomous driving car consisting of three main parts:perception, planning, control. Each main part is designed to recognize the real-time driving environment, make action plan based on finite state machine, and activate kinematic model based control. The proposed vehicle system copes with six major situations of urban environment driving, and we verified system through the simulation.

As recent research on deep learning methods has been actively conducted, a number of deep learning methods have been proposed. In this paper, we propose a method of removing the desired object from an image using generative adversarial networks(GANs) structure. We composed the network in which two GANs are fused. The first GAN erases the target object from the input image, and the second GAN generates an image that fills the empty space with the background. Through this network, we can erase the desired object from the input image and get an image with the erased part filled with the background without any object detection method. We show that the removal of people and vehicles from images of roads using the CityScapes Dataset.

To successfully implement SLAM based on semantic information, object recognition is essential. In our semantic SLAM approach, the robot should localize itself knowing only the pose of the surrounding objects. The implicit information in TOSM contains conceptual knowledge, in which we stored data that cannot be perceived by sensors only. However, it needs to distinguish not only an object class, but also which specific object instance a given detected object is related to. In many approaches, objects are recognized by detecting feature points and representing them as descriptors. There are several types of descriptors for feature points, such as SIFT and SURF. There are also descriptors describing a whole object instead of just feature points, like GOOD or HOOD. We suggest a new semantic descriptor, which includes more high-level information, and propose a process to recognize accurately through semantic analysis by semantic descriptors. In this paper, we introduce about our semantic descriptor model while giving some example cases, and then describe the process of data association by using the aforementioned descriptor.

In this paper, we propose a new control method for manipulator that allows changing motion immediately and flexible even in sudden situations. The reason is that in the future production process, human and robots will collaborate, or the robot will recognize an environment by itself. We defined linear motion and curve motion method of a 3DOF parallel robot. This control method can be controlled in real time. We simulated to verify motion and experimented with parallel robots and laser trackers. Using this control method, the adept motion experiment of the robot was performed, and the cycle time was 0.395 secs. The new control method was applied to the factory of a beverage company.

This study aimed to enable the recognition of the positions and rotation data of objects using the machine vision technology in the packaging process and the pick& place operations by robots using the data. For these objectives, this study proposed the methods of controlling the trigger signals of the camera and minimizing the imaging processing CPU resources in consideration of the recognition range of the campera, size of objects and speed of the conveyor belt. In addition, this study also tried to resolve the problem of an object being recognized as separate objects in the multiple frames of the camera.

A LABC (Laser-Assisted Bonding with Compression) bonder and NCF (Non-Conductive Film) were developed to increase the productivity of the bonding process for the advanced microelectronic packaging technology. The design features of a LABC make its UPH above 1,000. The NCF was applied to both of LAB and TCB (Thermal Compression Bonding Technology). The 780µm-thick daisy chain top and bottom chips with the minimum pitch of 30µm and bump number of about 27,000 were prepared and tested to verify the LABC and NCF technology. The effects of the laser power on the joints quality after the LABC bonding process were investigated and compared with the joints formed by the TCB technology. Finally, the SAT (Scanning Acoustic Tomography) images of the test vehicles before and after the TCO (Pressurized oven) were observed to check the voids in the NCF after the LABC bonding process.

This paper proposes a vision based high precision hand-eye self-calibration method to apply in the industrial robot. In the method, relationship between the robot end-effector and the camera is calculated using known accurate position of a designed chess board. This method can perform hand-eye calibration with high accuracy without operator intervention in the calibration process.

Any small defect is not permitted in the industry, so PLC real-time engine performance is very important for industry robot control system. Because these industrial characteristic, a new untested system can't be used in real field.

We present an efficient deterministic hypothesis generation algorithm for robust fitting of multiple structures based on the maximum feasible subsystem (MaxFS) framework. Despite its advantage, a global optimization method such as MaxFS has two main limitations for geometric model fitting. First, its performance is much influenced by the user-specified inlier scale. Second, it is computationally inefficient for large data. The presented MaxFS-based algorithm iteratively estimates model parameters and inlier scale and also overcomes the second limitation by reducing data for the MaxFS problem. Further it generates hypotheses only with top-n ranked subsets based on matching scores and data fitting residuals. This reduction of data for the MaxFS problem makes the algorithm computationally realistic. Our method, called iterative MaxFS with inlier scale estimation and subset updating (IMaxFS-ISE-SU) in this paper, performs hypothesis generation and fitting alternately until all of true structures are found. The IMaxFS-ISE-SU algorithm generates substantially more reliable hypotheses than random sampling-based methods especially as (pseudo-)outlier ratios increase. Experimental results demonstrate that our method can generate more reliable and consistent hypotheses than random sampling-based methods for estimating multiple structures from data with many outliers.

In recent days, vehicles have become equipped with electric system that assist and help drivers driving safe in highway. Lane Departure Warning and Lane Keeping Assistant System are one of those safe system. Sudden and inattentive lateral motion of vehicle due to drivers' fatigue, illness, inattention, and drowsiness are major causes of accidents in highway. In order to prevent and minimize any possible accidents due to lateral motion of vehicle, active steering control system is designed and simulated in this study. Activation and warning areas are defined for the control system with respect to the location of vehicle and parameters for vehicle dynamics. The current location of vehicle is obtained by Differential Global Positioning System (DGPS) and it can detect DGPS-based lanes then determine whether activates or not.

This paper presents development of simulators for mobile CT device. For mobile CT device, it is important to rotate the gantry system at constant speed. Rotating a gantry speed at constant speed is important because uniformity of angular distance among hundreds of taken X-ray images is highly related to quality of 3D reconstructed CT image. Therefore, in this paper, modeling of the gantry system and simulator is developed for control verification. Mobile CT device is a heavy system so it has a safety issues for engineer. Hence, it is preferred to develop a simulator which is really close to the real system. Then, implementation of the system will be easier after verification of the system using a simulator. The simulator which verifies control algorithm and sequence is presented using Lab view and Solid works and it can be implemented to the real system directly.

This paper presents a zero vibration control for mobile medical robot system when the gantry is rotated. ISO center needs to maintain its position while gantry is rotated to take multiple X-ray images for reconstructed 3D CT image. The gantry includes X-ray source and detector module causing unbalanced weight of rotor and the gantry is support in cantilever manner by support structure. This fact causes vibration of gantry in vertical axis, which is harmful for high quality of 3D CT image. In this paper, the manipulator is operated to give impulses to the system to reduce vibration and it is validated by experimental results.

Due to its restricted usage and accuracy in measuring extremely short interval of time, TDC (time to digital converter) embedded measurement devices are relatively expansive. Even if new applications are being developed in daily life as well as in industry, the cost condition of TDC based measurement systems needs to be improved. To reduce the deployment cost on a commercial scale, analogue interpolation method is preferred to digital interpolation method for most of TDCs. However, the analogue interpolation method does not provide robustness to temperature variation and non-uniformity of parts, which results in difficulty in maintaining the expected repeatability. In this paper, an auto-calibration method is proposed for robust operation and precise measurement of TDC under the condition of temperature variation and lack of parts uniformity.

The floating gate type of flash memory is impossible to scale down to beyond 45 nm due to the difficulty in scaling the tunnel oxide and the gate coupling ratio. Because of the difficulty in maintaining high gate coupling ratio and preventing cross talk between neighboring cells, NAND technology is forecasted to migrate gradually from floating gate devices (FG) to charge trapping memory (CTM). CTM are not sensitive to tunnel oxide damage since the charge is stored in discrete traps and one weak spot does not cause all stored charge to leak out as in floating gate devices. The NAND HC-TANOS flash cell has been generated in three dimensional TCAD tools with 38 nm gate length, 34 nm channel width and charge trapping structures. A structure of Al2O3 (15 nm)/Si3Na (6.5 nm)/SiO2 (4.5 nm) with TaN gate was employed as the gate stack. To study the effects of gate stack coverage on flash cell's performance, the shape of gate stack is varied while keeping all other structural parameters fixed.

This paper suggests the control technique that end-effector of manipulator can chase an object using an image gained from a stereo camera installed in a mobile robot platform and the camera positioned at the end of redundant manipulator in a wide working space. By using the stereo camera for searching the object in the wide working space, it is controlled to enable the end-effector of manipulator to approach the object. When the image of object is inputted to the camera equipped in end-effector, the manipulator is operated by reducing a position error between end-effector and object. Servo control system is verified through inter-layerpsilas autonomous navigation experiment using the mobile robotpsilas elevator with 8 DOF robot arms.

In this paper, the advanced process has been presented to remove the WSix peeling which was brought in sub-100 nm DRAM SRCAT(sphere-shaped-recess-channel-array transistor). The source of WSix peeling was proved to be the groove of gate poly film. We have completely solved the problems to adopt the gate-poly CMP (chemical mechanical polishing) process.

All these days, the active stereo vision system which can detect the certain object and measure the distance from the object through the camera's image have been studied. In the stereo vision system, it is the key point to search the certain object through the image and to track the object by controlling the motor which supports the camera based on the searched object information. Also, as the human being can estimate the distance from the object by using two eyes, the distance from the certain object can be estimated by using two cameras in the stereo vision system. When the certain object is located on the corner of image plane in the stereo vision system where the existing camera is fixed, an error occurs due to a lens's distortion, so reliability goes down. However, the cross stereo vision system always places the object in the middle of image and places the object in the middle of low distortion lens, so it can increase reliability of information gained from the system as its advantage. This paper is intended to implement the stereo vision system which can track the object and can measure the distance from the object in real time by applying the trigonometric measurement method and the robot kinematics to the cross-visual stereo vision system which is fabricate to be applied to the mobile robot and by distributing the controller's load, and to evaluate the performance by applying the mobile robot under an indoor lighting environment.

As a new alternative for the DRAM capacitor of 50 nm generation, Ru/Insulator/TiN (RIT) capacitor with the lowest Toxeq of 0.85 nm has been successfully developed for the first time. TiO/sub 2//HfO/sub 2/ and Ta/sub 2/O/sub 5//HfO/sub 2/ double-layers were used as dielectric materials. After full integration into 512 Mbits DRAM device, the RIT capacitor showed good electrical properties and thermal stability up to 550/spl deg/C and its time-dependent-dielectric-breakdown behavior sufficiently satisfied 10-year lifetime within a DRAM operation voltage.

The Jini technology is a suite of protocols and class libraries, which supports network-based plug-and-play of objects without configuring software or hardware of devices manually. It is specified for J2SE environment. Therefore, devices which have J2ME-environment cannot directly use Jini service. In this paper, we propose a method that devices having J2ME CLDC can use the Jini technology, present the private protocol and the architecture of surrogate object for J2ME-devices. We implemented and tested to which the J2ME-device is able to use Jini service through surrogate host. Developers can implement surrogate objects of other non-Jini devices easily by using our implementation.