Modeling and simulation of powered hip orthosis by pneumatic actuators

In this study, a simulation model for a powered hip orthosis (PHO) with air muscles to predict the gait of paraplegics is presented which can be used as a design tool for hip orthoses. Before simulation, mathematical models for a human dummy with an orthosis and a pneumatic muscle actuator were generated. For the air muscle, coefficients required were obtained by static and dynamic experiments of the air muscle and experiments for the valve controlling the air pressure. The computation was conducted on the ADAMS package together with MATLAB. Computer simulation of the flexion of hip joints by the pneumatic muscle results in similar values to those from gait analysis. With the development of a simulation model for a PHO, the gait simulation model using pneumatic muscles can be used to analyze and evaluate the characteristics and efficiency of a PHO by setting the input and boundary conditions.     

A MEMS guide plate for a high temperature testing of a wafer level packaged die wafer

This paper describes the design and fabrication of a MEMS guide plate, which was used for a vertical probe card to test a wafer level packaged die wafer. The size of the fabricated MEMS guide plate was 10.6 × 10.6 cm. The MEMS guide plate consisted of 8,192 holes to insert pogo pins, and four holes for bolting between the guide plate and the housing. To insert pogo pins easily, an inclined plane was defined at the back of each hole. Pitch and diameter of the hole were 650 and 260 μm, respectively. In order to define inserting holes and inclined planes at an exact position, silicon MEMS technology was used such as anisotropic etching, deep reactive etching and more. Silicon was used as the material of the guide plate to reduce alignment mismatch between the pogo pins and solder bumps during a high temperature testing. A combined probe card with the fabricated MEMS guide plate showed good x–y alignment and planarity errors within ±9 and ±10 μm at room temperature, respectively. In addition, x–y alignment and planarity are ±20 and ±16 μm at 125°C, respectively. The proposed MEMS guide plate can be applied to a vertical probe card for burn-in testing of a wafer level packaged die wafer because the thermal expansion coefficient of the MEMS guide plate and die wafer is same.     

Toward a human-like biped robot with compliant legs

Conventional models of bipedal walking generally assume rigid body structures, while elastic material properties seem to play an essential role in nature. On the basis of a novel theoretical model of bipedal walking, this paper investigates a model of biped robot which makes use of minimum control and elastic passive joints inspired from the structures of biological systems. The model is evaluated in simulation and a physical robotic platform by analyzing the kinematics and ground reaction force. The experimental results show that, with a proper leg design of passive dynamics and elasticity, an attractor state of human-like walking gait patterns can be achieved through extremely simple control without sensory feedback. The detailed analysis also explains how the dynamic human-like gait can contribute to adaptive biped walking.     

Hashtag-based topic evolution in social media

The rise of online social media has led to an explosion of metadata-containing user generated content. The tracking of metadata distribution is essential to understand social media. This paper presents two statistical models that detect interpretable topics over time along with their hashtags distribution. A topic is represented by a cluster of words that frequently occur together, and a context is represented by a cluster of hashtags, i.e., the hashtag distribution. The models combine a context with a related topic by jointly modeling words with hashtags and time. Experiments with real-world datasets demonstrate that the proposed models discover topics over time with related contexts effectively.     

Codevelopmental learning between human and humanoid robot using a dynamic neural-network model.

This paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural-network model, which is inspired by human parietal cortex functions. A humanoid robot, with a recurrent neural network that has a hierarchical structure, learns to manipulate objects. Robots learn tasks in repeated self-trials with the assistance of human interaction, which provides physical guidance until the tasks are mastered and learning is consolidated within the neural networks. Experimental results and the analyses showed the following: 1) codevelopmental shaping of task behaviors stems from interactions between the robot and a tutor; 2) dynamic structures for articulating and sequencing of behavior primitives are self-organized in the hierarchically organized network; and 3) such structures can afford both generalization and context dependency in generating skilled behaviors.     

Pocket extraction on proteins via the Voronoi diagram of spheres

Proteins consist of atoms. Given a protein, the automatic recognition of depressed regions, called pockets, on the surface of proteins is important for protein-ligand docking and facilitates fast development of new drugs. Recently, computational approaches have emerged for recognizing pockets from the geometrical point of view. Presented in this paper is a geometric method for the pocket recognition which is based on the Voronoi diagram for atoms. Given a Voronoi diagram, the proposed algorithm transforms the atomic structure to meshes which contain the information of the proximity among atoms, and then recognizes depressions on the surface of a protein using the meshes.     

Optimization of media processing workflows with adaptive operator behaviors

In this paper, we present the ARIA media processing workflow architecture that processes, filters, and fuses sensory inputs and actuates responses in real-time. The components of the architecture are programmable and adaptable; i.e. the delay, size, and quality/precision characteristics of the individual operators can be controlled via a number of parameters. Each data object processed by qStream components is subject to transformations based on the parameter values. For instance, the quality of an output data object and the corresponding processing delay and resource usage depend on the values assigned to parameters of the operators in the object flow path. In Candan, Peng, Ryu, Chatha, Mayer (Efficient stream routing in quality- and resource-adaptive flow architectures. In: Workshop on multimedia information systems, 2004), we introduced a class of flow optimization problems that promote creation and delivery of small delay or small resource-usage objects to the actuators in single-sensor, single-actuator workflows. In this paper, we extend our attention to multi-sensor media processing workflow scenarios. The algorithms we present take into account the implicit dependencies between various system parameters, such as resource consumption and object sizes. We experimentally show the effectiveness and efficiency of the algorithms.

The discovery of biomarkers for type 2 diabetic nephropathy by serum proteome analysis

Diabetic nephropathy (DN) is a serious kidney complication of diabetes, and constitutes the leading cause of end-stage renal disease. The earliest clinical evidence of DN is microalbuminuria, a term which refers to the appearance of small but abnormal amounts of albumin in the urine. However, screening methods for DN, such as biomarker assays, are yet to be developed for type 2 DN. In the present study, in an attempt to identify the biomarkers for initial diagnoses of type 2 DN, the protein profiles of human sera collected from 30 microalbuminuric type 2 diabetic patients were compared with those collected from 30 normoalbuminuric type 2 diabetic patients, via 2-DE. As a result, a total of 18 spots were determined to have different protein levels in the microalbuminuric patients. Twelve spots had lower protein levels of approximately 50%, and the other six had higher levels of approximately 100-300% as compared to the spots of normoalbuminuric patients. These spots were identified with ESI-Q-TOF (ESI-quadrupole-TOF) MS. Among the identified proteins, vitamin D-binding protein (DBP) and pigment epithelium-derived factor (PEDF) were verified by Western blotting. The results of this study indicate that the DBP may be employed as diagnostic and monitoring biomarkers of type 2 DN, contingent on further study into the matter.     

Parameter-free geometric document layout analysis

Automatic transformation of paper documents into electronic documents requires geometric document layout analysis at the first stage. However, variations in character font sizes, text line spacing, and document layout structures have made it difficult to design a general-purpose document layout analysis algorithm for many years. The use of some parameters has therefore been unavoidable in previous methods. The authors propose a parameter-free method for segmenting the document images into maximal homogeneous regions and identifying them as texts, images, tables, and ruling lines. A pyramidal quadtree structure is constructed for multiscale analysis and a periodicity measure is suggested to find a periodical attribute of text regions for page segmentation. To obtain robust page segmentation results, a confirmation procedure using texture analysis is applied to only ambiguous regions. Based on the proposed periodicity measure, multiscale analysis, and confirmation procedure, we could develop a robust method for geometric document layout analysis independent of character font sizes, text line spacing, and document layout structures. The proposed method was experimented with the document database from the University of Washington and the MediaTeam Document Database. The results of these tests have shown that the proposed method provides more accurate results than previous ones