Toshiki Takeuchi

cljam: a library for handling DNA sequence alignment/map (SAM) with parallel processing.

BackgroundNext-generation sequencing can determine DNA bases and the results of sequence alignments are generally stored in files in the Sequence Alignment/Map (SAM) format and the compressed binary version (BAM) of it. SAMtools is a typical tool for dealing with files in the SAM/BAM format. SAMtools has various functions, including detection of variants, visualization of alignments, indexing, extraction of parts of the data and loci, and conversion of file formats. It is written in C and can execute fast. However, SAMtools requires an additional implementation to be used in parallel with, for example, OpenMP (Open Multi-Processing) libraries. For the accumulation of next-generation sequencing data, a simple parallelization program, which can support cloud and PC cluster environments, is required.ResultsWe have developed cljam using the Clojure programming language, which simplifies parallel programming, to handle SAM/BAM data. Cljam can run in a Java runtime environment (e.g., Windows, Linux, Mac OS X) with Clojure.ConclusionsCljam can process and analyze SAM/BAM files in parallel and at high speed. The execution time with cljam is almost the same as with SAMtools. The cljam code is written in Clojure and has fewer lines than other similar tools.

Influencing driver behavior through future expressway traffic predictions

Unlike trains or buses, automobiles are essentially uncontrollable for road management companies. However, we can influence driver behavior to a certain degree by displaying appropriate traffic information. When taking a break at the rest area of an expressway, many drivers are unaware of the future traffic conditions along the highway toward their destination. We propose a method for changing the drivers departure time by predicting the future traffic conditions and informing the driver on how long the driver will expect to wait in a traffic jam based on the time at which the driver chooses to depart from the rest area. We created a prototype system for implementing the proposed method using the drivers smartphone and big data regarding the traffic conditions on an expressway in real-time. In this paper, we report the survey results of an elementary questionnaire regarding the proposed method.

A task-management system using future prediction based on personal lifelogs and plans

People who are busy generally have to manage a great variety of tasks. But sometimes, they fall behind in minor tasks and gradually, even without them noticing, a huge backlog piles up, far beyond the persons capacity to complete them well and on time. We proposed a task-management system that predicts a users future state on the basis of the users lifelog and plans, using a simple linear regression model. We implemented the system using a smartphone and estimated its usefulness with a user test. As a result, the users of our system saw their future diaries and tried to alter their current daily activities.

Interactive interface for expressway travel planning with traffic predictions

Though expressway administrators present drivers with traffic congestion information, the drivers cannot obtain sufficient practical information to avoid traffic congestion, determine how much congestion they will encounter or know when they will arrive at their destination. Therefore, we propose an interactive interface allowing the drivers to make a driving plan on an expressway with traffic predictions, and thus change their driving behavior. By visualizing traffic predictions using a diagram with two time axes, drivers can look at multiple futures interactively. Thus, they can obtain enough information to avoid traffic congestion. We compared our interface with conventional traffic congestion presentations, and also investigated its feasibility in a real environment by distributing our interface as an Android application. Our results showed that drivers were able to make a driving plan more efficiently using our interface than with conventional methods, and then follow their planned route on an expressway in a real environment.

Visualization of simultaneous experiences by multi sided recording of an event

Many people have their own camera or recording devices such as cellar phones and digital cameras. When there is a big event, a lot of pictures and movies are taken from various places at the same time. People want to record events with their digital devices as a memory or remembrance. We have some services to share these photos and movies, however, there is no viewer suitable to summarize and integrate these photos and movies for one event. Especially, when one event does not occur at one place but occur in a large area, it is difficult to visualize them. In this paper, we propose a novel viewer which enable people to see various experiences occurred at the same time. The viewer provides us three-dimensional view which includes space axis and time axis. We selected an event that occur in a large area, “the Last Run of the Express Noto”. The Express Noto is a train that runs from Tokyo to Kanazawa in Japan and takes about 7 hours. There is the last run event of the Express Noto in March, 2010. We recorded the event various kinds of recording methods, e.g., a digital camera, an portable movie camera, a voice recorder, tweets at “Twitter” with more than 10 people. Then we apply our data to our viewer that can visualize them three-dimensionally for easy understanding the expanse of simultaneous experience information. For evaluation of our system, we demonstrated this system at “The Railway Museum” in Japan, and find out usefulness which its used at museum.