Scaled Jacobian transpose based control for robotic manipulators

This paper presents a scaled Jacobian transpose based control method for robotic manipulators as a modification of a conventional Jacobian transpose based method. The proposed method has several advantages such as it shows faster convergence and better tracking performance than the conventional method, furthermore, it does not have any singularity problem similar to the conventional method. The scaled Jacobian transpose is obtained by collecting each pseudoinverse of the column vector of the Jacobian matrix. The proposed method performs a given task well under singular configurations while minimizing the task error. Finally, a few comparative studies with the conventional method are provided to show the effectiveness of the proposed method through simulations.     

Direct equivalence between geometric conditions and algebraic conditions for discrete-time nonlinear observer

Unlike the continuous-time case, algebraic necessary and sufficient conditions for a single output discrete-time system to be state equivalent to a nonlinear observer canonical form have been found and are easier to verify for those who are not accustomed to differential geometry. The geometric conditions look very different from the algebraic conditions. In this paper, we show direct equivalence of the geometric conditions and the algebraic conditions in order to enhance the understanding of the geometric conditions.     

A microfluidic device for thermal particle detection

We demonstrate the use of heat to count microscopic particles. A thermal particle detector (TPD) was fabricated by combining a 500-nm-thick silicon nitride membrane containing a thin-film resistive temperature detector with a silicone elastomer microchannel. Particles with diameters of 90 and 200 μm created relative temperature changes of 0.11 and ?0.44 K, respectively, as they flowed by the sensor. A first-order lumped thermal model was developed to predict the temperature changes. Multiple particles were counted in series to demonstrate the utility of the TPD as a particle counter.     

Virtual target tracking of mobile robot and its application to formation control

A virtual target tracking approach is proposed for kinematic control of mobile robot. In the controller, linear and angular velocity inputs are generated by using the local data of robot position and orientation along with the estimated velocity of target object. Applying the proposed approach to a cooperative robot group with arbitrary number of multiple mobile robots, it is possible to create various robot formations for cooperative navigation and tracking of moving object. The developed controller is shown to be stable and convergent through theoretical proof and a series of experiments.     

Leakage current in a Si-based nanopore structure and its influence on noise characteristics

We have measured leakage current in a silicon substrate-based nanopore membrane device immersed in an aqueous environment which typically shows the current level of few nA. This current level is compared with the measured current density (400 nA/cm² at 1 V) from the pristine Si wafer (p-type, 10¹⁶/cm³ boron doping) indicating that the exposed Si surface in a nanopore membrane device acts as an electrochemical reaction site. The leakage current is drastically reduced from >10 nA to <100 pA at 1 V by the deposition of a dielectric layer to the Si-based nanopore membrane device. We also noted that the root-mean-square noise of the ionic current is also reduced from 38 to 28 pA in correlation with the reduction of leakage current, indicating that electrochemical reaction provides one of the major sources of noise.     

Design optimization of a laser printer cleaning blade for minimizing permanent set

When a cleaning blade in a laser printer is excessively deformed, immoderate permanent set can result, leading to weaker nip pressure between the cleaning blade and OPC drum that worsens its cleaning performance and printing quality. In this study, the correlation of the permanent set with stress and strain was investigated through tensile tests with rubber test specimens. Based on the experimental results, the maximum von-Mises stress value was used to quantify the permanent set. A design optimization problem was formulated to minimize the maximum von-Mises stress while satisfying the design constraints for maintaining appropriate contact between the cleaning blade and the OPC drum. We employed metamodel-based design optimization using design of experiments, metamodeling and an optimization algorithm to circumvent the difficulty of structural analyses at some design points. Using the proposed design approach, the optimal maximum von-Mises stress was reduced by 40.2 % compared to the initial stress value while all the design constraints were satisfied. In order to verify the validity of our design optimization result, we manufactured the cleaning blades according to the optimum design solution and performed permanent set and printer tests. The test results clearly showed the validity of our design optimization result.     

A strain based topology optimization method for compliant mechanism design

The Energy based topology optimization method has been used in the design of compliant mechanisms for many years. Although many successful examples from the energy based topology optimization method have been presented, optimized configurations of these designs are often very similar to their rigid linkage counterparts; except using compliant joints in place of rigid links. These complaint joints will endure large strain under the applied forces in order to perform the specified motions which are very undesirable in a compliant mechanism design. In this paper, a strain based topology optimization method is proposed to avoid a localized high strain of the compliant mechanism design, which is one of the drawbacks using strain energy formulation. Therefore, instead of minimizing the strain energy for structural rigidity, a global effective strain function is minimized. This is done in order to distribute the strain within the entire mechanism while maximizing the structural rigidity. Furthermore, the physical programming method is adopted to accommodate both flexibility and rigidity design objectives. Design examples from both the strain energy based topology optimization and the strain based method are presented and discussed.     

Multiple categorizations of products: cognitive modeling of customers through social media data mining

As various forms of social media are spreading, we often witness that an idea of an individual user drives macroscopic changes. From the perspectives of product development and marketing, the opinions left by potential consumers in online social network can generate big ripple effects. This study analyzes the user opinions in online space to grasp preferences toward various products psychologically categorized by users. We also suggest an aspect of the market mentally configured by users using network modeling while following the framework of economic sociology. Existing analyses on online market place are mainly dealing with structural issues such as inter-actor relationships and status measurement. This study, however, analyzes complex preferences regarding diverse products and brands and derives a new model for inter-market connections. We expect that our study will provide important consequences on digital marketing and community design of corporations planning word of mouth effect in online space.     

Coronary heart disease optimization system on adaptive-network-based fuzzy inference system and linear discriminant analysis (ANFIS–LDA)

Coronary heart disease is a great concern in the field of healthcare, and one of the main causes of death across the world. In the USA, as in Europe, it is responsible for the highest mortality rate. Although the risk of coronary heart disease has been recognized, few studies have been conducted on this topic. On the other hand, computer science has become an important part of our lives. The use of medicine and medical science-related artificial intelligence facilitating the diagnosis and analysis of diseases and health problems is attracting considerable attention. The present study focuses on the determination of the optimum method for using artificial intelligence in a clinical decision support system in order to provide a solution and diagnosis regarding the research and medical issues related to the application of such a system. In the present study, we have developed a prediction model capable of the risk assessment of coronary heart disease by optimizing an adaptive-network-based fuzzy inference system (ANFIS) and linear discriminant analysis (LDA) on the basis of the dataset of Korean National Health and Nutrition Examinations Survey V. The ANFIS–LDA method, which is optimized using a hybrid method, exhibits a high prediction rate of 80.2 % and is more efficient and effective than the existing methods. We expect that our study to contribute to the prevention of coronary heart disease.     

Development of head detection and tracking systems for visual surveillance

This paper proposes a technique for the detection of head nod and shake gestures based on eye tracking and head motion decision. The eye tracking step is divided into face detection and eye location. Here, we apply a motion segmentation algorithm that examines differences in moving people’s faces. This system utilizes a Hidden Markov Model-based head detection module that carries out complete detection in the input images, followed by the eye tracking module that refines the search based on a candidate list provided by the preprocessing module. The novelty of this paper is derived from differences in real-time input images, preprocessing to remove noises (morphological operators and so on), detecting edge lines and restoration, finding the face area, and cutting the head candidate. Moreover, we adopt a K-means algorithm for finding the head region. Real-time eye tracking extracts the location of eyes from the detected face region and is performed at close to a pair of eyes. After eye tracking, the coordinates of the detected eyes are transformed into a normalized vector of x-coordinate and y-coordinate. Head nod and shake detector uses three hidden Markov models (HMMs). HMM representation of the head detection can estimate the underlying HMM states from a sequence of face images. Head nod and shake can be detected by three HMMs that are adapted by a directional vector. The directional vector represents the direction of the head movement. The vector is HMMs for determining neutral as well as head nod and shake. These techniques are implemented on images, and notable success is notified.