There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world

Robust Model-Based Fault Diagnosis for Dynamic Systems

비만아 부모의 돌봄 경험: q 방법론

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

In this paper, binary classification methods using support vector machines (SVM) obtained from one-class learning and two-class learning are introduced. Firstly, an application of deep CNN (DCNN) for visual inspection is developed and is trained using a large number of images to inspect undesirable defects seen in resin molded articles. Then, the trained DCNN named sssNet and well-known Alexnet are respectively incorporated with two kinds of one-class learning based SVMs to classify sample images with high recognition rate into accept as OK category or reject as NG category, in which compressed feature vectors obtained from the DCNNs are used as the inputs for the SVMs. The performances of two SVMs obtained from one-class learning are compared and evaluated through training and classification experiments. Then, another SVM obtained from two-class learning is introduced. Finally, a template matching technique is further applied to extract important target areas from original training and test images. This will be able to enhance the reliability and accuracy for binary classification.

Fusion Method of Convolutional Neural Network and Support Vector Machine for High Accuracy Anomaly Detection

The Polishing Robot for PET Bottle Molds Using a Fuzzy Force Controller

A fuzzy-energy regions based switching method has been studied to control Underactuated manipulators. The switching rule of this method was designed on sub-energy regions with several boundary curves represented by fuzzy reasoning. However, it was pointed out, through some simulations, that the number of switching times for partially stable controllers increased according to the initial conditions and design parameters. The present paper introduces a novel energy definition in the sense of monotonic decreasing and develops the corresponding switching rules with such energy, to reduce the number of switching times. The effectiveness of the proposed approach is verified through some simulations for a 2-link Underactuated manipulator.

A switching control of underactuated manipulators by introducing a definition of monotonically decreasing energy

There exist various studies on underactuated control methods so far, but most of them are conﬁned into the case of systems with two inputs, and therefore there are a few studies for systems with three or more inputs. In this paper, a ﬁre truck robot that is an underactuated system with three inputs is considered as a controlled object, and a switching control method based on an invariant manifold theory is proposed for stabilizing it,where a chained form model is assumed to be used as a canonical model. It is expected that each state of the controlled object will be converged smoothly to the origin by using this type of control. The effectiveness of the proposed method is demonstrated through simulations.

Stabilization of a Fire Truck Robot by an Invariant Manifold Theory

The rings event is one of men's apparatus gymnastics, and has free-floating characteristics at the gripping point that do not exist in the other gymnastic events. In this paper, we propose a rings gymnastic robot intended to apply it to the coaching. Joint torque in exercises is informative for the coaching and gymnasts can easily obtain the knowledge to realize exercises if a control law of the torque is represented as "if-then" rules. Therefore, we adopt fuzzy control as a control strategy for the rings gymnastic robot. The purpose of this paper is to acquire suitable fuzzy rules for realizing a series of exercises, which is a handstand from backward giant circle. Simulation results show the effectiveness of the fuzzy rules and a guideline for the coaching can be read from the fuzzy rules.

Keigo Watanabe

Papers

Fusion Method of Convolutional Neural Network and Support Vector Machine for High Accuracy Anomaly Detection

The Polishing Robot for PET Bottle Molds Using a Fuzzy Force Controller

A switching control of underactuated manipulators by introducing a definition of monotonically decreasing energy

Stabilization of a Fire Truck Robot by an Invariant Manifold Theory

A study on rings gymnastic robot: (Fuzzy control rules for realizing exercises)