This paper introduces a reusable framework for analytics governance accelerating the use of data and analytics across organizations. The Analytics Governance Framework (AGF) is a set of guiding principles for streamlining the work of managers, analytics practitioners, and data management practitioners. The guiding principles of analytics work are designed to have check points where both managers and analytics practitioners work toward the same outcome. These principles facilitate communication and coordination on the project unique data requirements between practitioners of data management and analytics. This framework enables client organizations to optimize the number of analytics projects they are undertaking to achieve business transformation and to shorten the time of an analytics project to achieve the business impact.

In this paper, we propose a novel continuum robot based on closed loop elastic structure with bending and twisting. The proposed continuum robot consists of an elastic tube and a closed loop arm completely independent from the tube. The closed loop arm is a simple thin belt-shaped elastic strip which has two translational joints and one rotary degree of freedom. Here we found that when the closed loop arm was inside the tube and the one side of the translational joint was pushed or pulled, the tube could be bent easily. Based on this basic result, we proposed three types of the closed loop arm shape using bending and twisting of the elastic strip and showed that these arms made the tube deformed into completely different shapes including 180 degrees of rotation. The proposed mechanism was applied to two prototypes. One of them is the magnet resonance compatible manipulator which consists of the β titanium pipe of outer radius of 3 mm and the wall thickness of 0.2 mm and the polyetheretherketone resin elastic strip.

MRI-guided percutaneous liver interventions have been investigated by researchers as an alternative to CT-guided procedures as it is non-invasive and provides greater soft tissue details. In practice, however, repeated needle insertion is still required to reach desired positions on trial-and-error basis. To minimize the needle attempt and procedural time, we designed a robotic needle guidance device that provides needle insertion angle guidance at skin entry using two rotational joints structured for remote-center-of-motion manipulation. To evaluate the mechanism and clinical feasibility, we fabricated a proof-of-concept prototype that can be manually operated. As preliminary design evaluation, we conducted a retrospective clinical study of 13 MRI-guided abdominal biopsies to determine if the proposed mechanism and device can provide necessary needle insertion angles in MRI-guided liver biopsy procedures. The number of needle insertion attempts per biopsy was also measured. To confirm the kinematic design of the double ring remote-center-of-motion mechanism and to identify any procedural difficulties, we conducted a phantom targeting experiment. The retrospective clinical study showed that the 80 degree insertion angle coverage of the device is sufficient for clinical cases, and an average of five needle insertion attempts per biopsy in conventional MRI-guided biopsy can be reduced by the proposed device. A phantom targeting experiment confirmed that the unique kinematic design was successfully implementation in the targeting.

In this paper, we propose a novel closed loop elastic structure which can generate snap-through buckling with bending and distortion. The proposed mechanical closed loop structure consists of two rotary shafts and a belt-shaped elastic material which two ends are connected to one active rotary shaft and one free joint type shaft, respectively. Driving the active rotary shaft continuously, we can obtain impulsive motion by using snap-through buckling repeatedly. The change of the driving torque and the angular momentum generated snap-through buckling are shown by numerical simulations. From these results, it is shown that an offset parameter of the proposed structure is useful for generating impulsive turning motions of the compact swimming robot. The proposed mechanism is applied to a compact swimming robot which can turn impulsively at a maximum rate of 135 deg/s underwater.

In this paper, we propose a robotic catapult based on closed elastica utilizing bending and twisting deformation of an elastic strip. By using snap-through buckling generated from not only bend but also twist of thin rectangle elastic strip, impulsive forces can be generated repeatedly by the frequency of 3[Hz] without changing added torque directions. The compact jumping robot based on the proposed robotic catapult can leap over 950[mm] away. In addition, by setting the parameters appropriately to make the best use of generating impulsive forces with high frequency, it can perform repeated low-altitude jumping motions with about 1.06[m/s] velocity including quick step of about 0.152[s].

In this paper, we propose a new asymmetric robotic catapult based on the closed elastica. The conventional robotic catapults based on the closed elastica which the authors developed are the robotic elements for generating impulsive motions by utilizing a snap-through buckling. In a typical closed elastica, the two ends of an elastic strip are fixed to a passive rotational joint and an active rotational joint, respectively. Here we found that by adding only a range limitation to the passive rotational joint, compared to the conventional type, the deforming shape of the elastic strip becomes more complicated and 40% more elastic energy can be stored. Using this modification, we can develop a compact jumping robot which is able to leap over 700[mm] away and 200[mm] high.

In this paper, we propose a new robotic catapult with a high stiffness endpoint. The conventional robotic catapults based on the closed elastica are robotic elements for generating impulsive motions by utilizing the snap-through buckling. In a typical robotic catapult, the two ends of an elastic strip are fixed to a free joint and an active joint, respectively. Here we found that by adding only the high stiffness at the free joint, compared to the conventional type, more elastic energy can be stored and release surely without loss of a characteristic of generating impulsive motion repeatedly. By utilizing the high stiffness endpoint, we develop a faster impulsive swimming robot than the conventional one.

Two types of robotic catapults based on the closed elastica are proposed as robotic elements for generating impulsive motions. To obtain impulsive motions, these catapults utilize the snap-through buckling of an elastic material induced by applying driving torques to the ends of the elastic strip. In this paper, we show the effectiveness of the various types of the robotic catapults based on the kinematics and statics of a serialchain approximation model. The numerical simulations show that these catapults can increase the elastic energy necessary for impulsive motions even if the driving torques decrease.

This paper describes two methods for detecting word segments and their morphological information in a Japanese spontaneous speech corpus, and describes how to tag a large spontaneous speech corpus accurately by using the two methods. The first method is used to detect any type of word segments. The second method is used when there are several definitions for word segments and their POS categories, and when one type of word segments includes another type of word segments. In this paper, we show that by using semi-automatic analysis, we achieve a precision of better than 99% for detecting and tagging short-unit words and 97% for long-unit words; the two types of words that comprise the corpus. We also show that better accuracy is achieved by using both methods than by using only the first.

This paper describes two methods for detecting word segments and their morphological information in a Japanese spontaneous speech corpus, and describes how to tag a large spontaneous speech corpus accurately by using the two methods. The first method is used to detect any type of word segments. The second method is used when there are several definitions for word segments and their POS categories, and when one type of word segments includes another type of word segments. In this paper, we show that by using semi-automatic analysis we achieve a precision of better than 99% for detecting and tagging short words and 97% for long words; the two types of words that comprise the corpus. We also show that better accuracy is achieved by using both methods than by using only the first.

A sharable software repository for Japanese LVCSR (Large Vocabulary Continuous Speech Recognition) is introduced. It is designed as a baseline platform for research and developed by researchers of different academic institutes under a governmental support. The repository consists of a recognition engine (Julius), Japanese acoustic models and statistical language models as well as Japanese morphological analysis tools. These modules can be easily integrated and replaced under a plug-and-play framework, which makes it possible to fairly evaluate components and to develop specific application systems. Assessment of these modules and systems in a 20000-word dictation task is reported. The software repository is freely available to the public.

The ability to generate fair curves and surfaces is important in computer graphics (CG), computer-aided design (CAD), and other geometric modeling applications. In this paper, we present an iteration-based algorithm for generating fair polygonal curves and surfaces that is based on a new discrete spring model. In the spring model, a linear spring, whose length approximately represents a curvature radius, is attached along the normal line of each polygon node. Energy is assigned to the difference of the lengths, that is, the difference in curvature radius, of neighboring springs. Our algorithm then minimizes the total energy by an iterative approach. It accepts as inputs (1) an initial polygonal curve (surface), which consists of a set of polygonal segments (faces) and a set of nodes as polygon-vertices, and (2) constraints for controlling the shape. The outputs are polygonal curves (surfaces) with smooth shapes. We also describe a method for improving the performance of our iterative process to obtain a linear execution time. Our algorithm provides a tool for the fair curve and surface design in an interactive environment.

It is very important to improve software quality using program analysis and measurement tools and the SQA (Software Quality Assurance) method at the appropriate points during the process of development. In many development departments, there is often not enough time to evaluate and use the tools and the SQA method or to accumulate the know-how for effective use. This paper describes the support activity of a software quality analysis and measurement service which is performed by our laboratory team within the company as a third-party independent staff group. We call this activity HQC (High Quality software creation support virtual Center). The purpose of this activity is as follows. First we improve the software quality engineering process in the development department, for example, we help them to increase efficiency of review or testing. To accomplish this, we use program static analysis tools to detect fault-prone software components. Next we assist in starting their own self-improvement process. In addition, we provide service activity to many development departments concurrently. We have been making progress with these activities, and some development departments have begun to establish improvement processes themselves.

The project of Japanese LVCSR (Large Vocabulary Continuous Speech Recognition) platform is introduced. It is a collaboration of researchers of different academic institutes and intended to develop a sharable software repository of not only databases but also models and programs. The platform consists of a standard recognition engine, Japanese phone models and Japanese statistical language models. A set of Japanese phone HMMs are trained with ASJ (Acoustic Society of Japan) databases of 20K sentence utterances per each gender. Japanese word N-gram (2-gram and 3-gram) models are constructed with a corpus of Mainichi newspaper of four years. The recognition engine JULIUS is developed for assessment of both acoustic and language models. The modules are integrated as a Japanese LVCSR system and evaluated on 5000-word dictation task. The software repository is available to the public.