Time filter

Source Type

Tokyo, Japan

Nakagawa T.,Tohoku Institute of Technology | Kimura S.,NTT Software
Earth, Planets and Space | Year: 2011

The solar wind interaction with a non-magnetized, electrically non-conducting body is studied using a two- dimensional electromagnetic full particle simulation. The solar wind magnetic field is introduced into the simulation scheme as an initial condition together with the electric field generated by the motion of the solar wind. The solar wind magnetic field controls the direction of the thermal flow of the electrons and causes an asymmetry of the negative charging of the downstream-side surface. The negative charging and the potential drop are largest at the position where the solar wind magnetic field is perpendicular to the surface of the non- magnetized body. In the absence of photoelectrons, the solar wind electrons begin to be expelled by the negative charging at the terminator and then flow away along the field line producing streaks of enhancements of the electron density. © The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS); The Seismological Society of Japan; The Volcanological Society of Japan; The Geodetic Society of Japan; The Japanese Society for Planetary Sciences; TERRAPUB.

Yamato Y.,NTT Software
Journal of Cloud Computing | Year: 2015

We propose here a technique for automatic verification of software patches for user virtual environments on Infrastructure as a Service (IaaS) Cloud to reduce the cost of verifying patches. IaaS services have been spreading rapidly, and many users can customize virtual machines on IaaS Cloud like their own private servers. However, users must install and verify software patches of the OS or middleware installed on virtual machines by themselves. This task increases the user’s operation costs. Our proposed method replicates user virtual environments, extracts verification test cases for user virtual environments from a test case database (DB), distributes patches to virtual machines in the replicated environments, and executes the test cases automatically on the replicated environments. To reduce test cases creation efforts, we propose an idea of two-tier abstraction which groups software to software groups and function groups and selects test cases belonging to each group. We applied the proposed method on OpenStack using Jenkins and confirmed its feasibility. We evaluated the effectiveness of test case creation efforts and the automatic verification performance of environment replications, test cases extractions, and test case executions. © 2015, Yamato; licensee Springer.

Fujiwara Y.,NTT Software | Irie G.,Nippon Telegraph and Telephone | Kuroyama S.,California Institute of Technology | Onizuka M.,Osaka University
Proceedings of the VLDB Endowment | Year: 2014

Manifold Ranking is a graph-based ranking algorithm be- ing successfully applied to retrieve images from multimedia databases. Given a query image, Manifold Ranking com- putes the ranking scores of images in the database by ex- ploiting the relationships among them expressed in the form of a graph. Since Manifold Ranking effectively utilizes the global structure of the graph, it is significantly better at finding intuitive results compared with current approaches. Fundamentally, Manifold Ranking requires an inverse ma- trix to compute ranking scores and so needs O(n3) time, where n is the number of images. Manifold Ranking, un- fortunately, does not scale to support databases with large numbers of images. Our solution, Mogul, is based on two ideas: (1) It efficiently computes ranking scores by sparse matrices, and (2) It skips unnecessary score computations by estimating upper bounding scores. These two ideas re- duce the time complexity of Mogul to O(n) from O(n3) of the inverse matrix approach. Experiments show that Mogul is much faster and gives significantly better retrieval quality than a state-of-the-art approximation approach. © 2014 VLDB Endowment 21508097/ 14/12.

The hosted cloud-based environment will provide a highly scalable end-to-end Platform-as-a-Service (PaaS) business analytics solution for the Japanese market. The offering, named InfoCabina Yellowfin Cloud, combines an initial five-user license for Yellowfin’s 100 percent Web-based consumer-oriented BI solution, and Appresso’s DataSpider ETL tool, with either Amazon’s Relational Database Service (RDS) or Amazon Redshift – AWS’s petabyte-scale columnar data warehouse service for Big Data Analytics. Maintenance, support and upgrades are also included in the monthly subscription-based licensing model, which contains no up-front costs. NTT Software, a subsidiary company of Japanese telecommunications giant NTT, will assist clients with implementation, integration and ongoing management of the InfoCabina Yellowfin Cloud solution. “As a 100 percent Web-based BI solution, Yellowfin is a fantastic fit for deploying Cloud BI on the AWS platform,” said Yellowfin CEO, Glen Rabie. “By partnering with Appresso, NTT Software and AWS, the Japanese market can take advantage of our combined technology and implementation strengths. Together, we are delivering a total PaaS reporting and analytics environment with an incredibly affordable total cost of ownership. “With NTT Software overseeing deployment, configuration, integration and ongoing management of the InfoCabina Yellowfin Cloud solution, Japanese organizations can quickly start performing sophisticated Big Data Analytics, and seamlessly scale throughout the enterprise, as data volumes and usage demands increase.” President and CEO of NTT Software Corporation, Shinichi Yamada, said it was exciting to be involved in a strategic partnership that had the ability to create a new Cloud BI market in Japan. “NTT Software Corporation has agreed to be the official delivery and integration partner for InfoCabina in Japan,” said Yamada. “We’ve done so because we believe the Yellowfin – Appresso – Amazon offering delivers a unique set of innovative technologies that will make cloud-based reporting and analytics financially and technologically accessible to organizations of all sizes in the Japanese market. “NTT Software Corporation will deliver InfoCabina Yellowfin Cloud as a fully-managed hosted environment. Japanese organizations will have all the components needed to quickly begin loading and exploring Big Data at scale in a secure hosted environment on AWS. “Combining Yellowfin’s BI platform, Appresso’s ETL and Amazon’s RDS or Redshift technologies, with NTT Software Corporation’s professional services package, will deliver everything an organization needs to generate fast BI return on investment – from environment set-up, data collection, processing and analysis, to ongoing maintenance and support.” Yamada said that NTT Software Corporation would also offer additional and ongoing consulting, report development and training services to assist clients to “attain superior return on investment” from their InfoCabina Yellowfin Cloud environment. Apresso President, Kazutoshi Ono, said Apresso was “excited to be involved with Yellowfin, Amazon and NTT Software to deliver this pioneering PaaS solution.” “InfoCabina will enable our Japanese clients to develop a fully-fledged world-class BI environment in a very short space of time,” said Ono. “With the data linkage and automation features of Appresso’s ETL tool, DataSpider, InfoCabina clients will be able to quickly and easily combine data from multiple source systems, deliver intuitive reporting and analytics throughout the enterprise with Yellowfin, and power Big Data Analytics with Amazon Redshift.” Senior Manager for Strategic Alliances at Amazon Data Services Japan, Yoshihiro Konno, said that offering Yellowfin to the Japanese market as a fully-managed hosted solution on AWS would help drive Yellowfin’s growth throughout Japan. “Amazon Data Services Japan welcomes the fact that NTT Software has started to provide Yellowfin on AWS,” said Konno. “The scalability of AWS, combined with NTT Software’s fully-managed service delivery, will make sophisticated and intuitive BI capabilities available to companies that may have struggled with the cost and complexities of BI in the past. “InfoCabina on AWS is an ideal service model for those organizations wanting to easily grow their BI environment inexpensively over time as their business grows – they can seamlessly scale up and down as usage demands and data capacities change. With InfoCabina on AWS, organizations will be able to begin performing data analysis quickly, at low costs, with minimal internal resources.” The announcement of the joint InfoCabina Yellowin Cloud solution follows Yellowfin’s release of a free Cloud BI offering on the AWS Marketplace in November 2014 (AWS usage fees apply). The complimentary trial enables organizations to deploy an enterprise-grade BI solution in minutes, which includes a free 12-month three-user subscription license for Yellowfin. Yellowfin’s credentials as a cloud-based BI solution were also recently recognized in the Business Applications Research Center’s (BARC) The BI Survey 14 – the world’s largest annual survey of BI users. Yellowfin was voted the top ranked Cloud BI solution, in the ‘Dashboard’ and ‘Ad-hoc Reporting’ Vendor Peer Groups, for the third year in a row. “Cloud BI is clearly a space that Yellowfin dominates,” said Founder and CEO of BARC, Dr Carsten Bange. “Yellowfin has obviously invested heavily in Cloud BI and was early to market with its solution. Yellowfin’s cloud-based clients reported strong achievement of the business benefits sought from their BI implementations.” NTT is an innovative ICT solutions business and one of the largest companies in Japan. NTT Software is wholly owned by Nippon Telegraph and Telephone Corporation (NTT), providing system integration and networking system solution services based on emerging technologies from NTT R&D laboratories. For more information, visit http://www.ntts.co.jp Appresso KK is a Japanese software vendor that develops, produces, distributes and maintains enterprise infrastructure, storage and integration solutions. Appresso KK has developed a strong reputation, particularly in Japan’s domestic market, for their Enterprise Application Integration, Business Process Management and collaboration products as well as software engineering services. Appresso KK’s flagship data collaboration and ETL product, DataSpider, has been installed at over 1500 end-user premises. Appresso serves a wide range of industries and businesses in Japan and internationally. For more information, visit http://www.appresso.com Yellowfin is a global Business Intelligence (BI) and analytics software vendor passionate about making BI easy. Founded in 2003 in response to the complexity and costs associated with implementing and using traditional BI tools, Yellowfin is a highly intuitive 100 percent Web-based reporting and analytics solution. Yellowfin is a leader in mobile, collaborative and embeddable BI as well as Location Intelligence and data visualization. Over 10,000 organizations, and more than one million end-users across 70 different countries, use Yellowfin every day. For more information, visit http://www.yellowfinbi.com Amazon Web Services (AWS) was launched in 2006, and provides a highly reliable, scalable, low-cost infrastructure platform in the cloud. AWS powers over one million enterprise, government and startup organizations in 190 countries around the world. For further media information, interviews, images or product demonstration, please contact: For regular updates and news, follow Yellowfin on Twitter (@YellowfinBI), LinkedIn (Yellowfin Business Intelligence) or email pr(at)yellowfin(dot)bi to subscribe to Yellowfin’s free e-newsletter.

Fujiwara Y.,NTT Software | Nakatsuji M.,Nippon Telegraph and Telephone | Shiokawa H.,NTT Software | Mishima T.,NTT Software | Onizuka M.,NTT Software
Proceedings of the ACM SIGMOD International Conference on Management of Data | Year: 2013

Personalized PageRank (PPR) has been successfully applied to various applications. In real applications, it is important to set PPR parameters in an ad-hoc manner when finding similar nodes because of dynamically changing nature of graphs. Through interactive actions, interactive similarity search supports users to enhance the efficacy of applications. Unfortunately, if the graph is large, interactive similarity search is infeasible due to its high computation cost. Previous PPR approaches cannot effectively handle interactive similarity search since they need precomputation or approximate computation of similarities. The goal of this paper is to efficiently find the top-k nodes with exact node ranking so as to effectively support interactive similarity search based on PPR. Our solution is Castanet. The key Castanet operations are (1) estimate upper/lower bounding similarities iteratively, and (2) prune unnecessary nodes dynamically to obtain top-k nodes in each iteration. Experiments show that our approach is much faster than existing approaches. Copyright © 2013 ACM.

Discover hidden collaborations