The Great East Japan Earthquake on March 11th, 2011 caused severe damage to the northern coast of the main island in Japan. Since then we have been working to help out the affected area in terms of IT support such as internetworking and providing PCs. Through our support activities we came across an interesting issue concerning collaboration with people from heterogeneous backgrounds. We call this problem disaster communications. In this paper we report our experiences during our support activities and our findings as well as some issues and our current work.

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“3.11”—the worst disaster in postwar Japanese history, consisting of the Great East Japan Earthquake (March 11, 2011), the subsequent tsunami and the nuclear accident at the Fukushima Daiichi power plant—taught us many valuable lessons. This paper reviews the disaster from a computer scientist's perspective, paying special attention to the problem of presenting data to the public, and discusses what we could do and can still do.

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The important roles of after school care programs are protecting the lives of students whose parents are working or unable to be at home after they finish school or on school holidays and helping them create self independence. We propose a learning support system for helping after school care students. The system is used for practicing the “Kuku” multiplication table and it has been implemented using the Kinect motion capture system to recognize “air characters” written by the body actions of learners. We conducted a trial to evaluate the proposed system by asking many students in after school care programs to participate and confirmed that this system was helpful for groups of students to learn. We explain here how we implemented the system, and report the results from the trial. We also suggest the future directions of the system.

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The number of electronic control units (ECUs) has increased to manage complicated vehicle systems. Many kinds of operating systems that run on ECUs exist: ITRON OS, OSEK OS, and so forth. Currently, developers implement the system control software according to the ITRON and OSEK specifications independently. For example, even though OSes provide similar functionalities, OSEK specifications have several differences from ITRON specifications such as scheduling policies (Non-preemptive scheduling), alarms, hook routines, and several system calls. Thus, when using legacy software following OSEK specifications on the ITRON OS, developers have to port the software to ITRON OS. This paper presents a component-based framework to fill the gap between OSEK and ITRON specifications by using TECS (TOPPERS Embedded Component System). The work required to port legacy OSEK applications built with TECS components to ITRON applications built for TECS is reduced by using our method. TECS is a high-level abstraction component system for enhancing the reusability of software. Examples for the characteristics of the framework are: (1) Non-preemptive scheduling tasks are implemented by changing the priority of the task to the highest priority; (2) The system works as the OSEK alarm based on a counter value, which is incremented at an arbitrary time interval; (3) OSEK hook routines are also available with a particular timing. Experimental results demonstrate that the overhead of the corresponding system calls compared to the original OSEK system calls is reduced to within 13.58µsec.

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Ensuring the integrity of logs is essential to reliably detect and counteract attacks because adversaries tamper with logs to hide their activities on a computer. Even though some studies proposed various protections of log files, adversaries can tamper with logs in kernel space with kernel-level malicious software (malware) because file access and inter-process communication are provided by an OS kernel. Virtual machine introspection (VMI) can collect logs from virtual machines (VMs) without interposition of a kernel. It is difficult for malware to hinder that log collection, because a VM and VM monitor (VMM) are strongly separated. However, complexity and unnecessary performance overhead arise because VMI is not specialized for log collection. This paper proposes a secure and fast log transfer method using library replacement for VMs. In the proposed method, a process on a VM requests a log transfer to a VMM using the modified library, which contains a trigger for a log transfer. The VMM collects logs from the VM and isolate them to another VM. The proposed method provides VM-level log isolation and security for the mechanism itself with low performance overhead.

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Probabilistic Packet Marking (PPM) is known to be one of the better defense methods against Denial of Service (DoS) attacks. However, most of the routers on the Internet are not yet ready for PPM. Before a new router that has the PPM function can be deployed, several challenges such as cost, operation, and availability must first be resolved. In this paper, we propose a device for transparent PPM that makes the target router PPM-capable. The device does not change the existing configuration of the router nor do existing routers have to be replaced. We implemented and evaluated our proposed device on Linux with excellent results.

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Large-scale massive heterogeneous data have been accumulated in various fields of scientific research and society. As a result, discovering new knowledge by linking sensing and science data, such as web archives, has attracted attention. We developed a Knowledge Language Grid (KLG) system that combines multiple asset data from different providers and allows users to use or re-use them. KLG structures a great quantity of information that can be confidential for individuals, companies, or institutions, but it can also be misused or disclosed to inappropriate people. In this paper, we propose a risk assessment framework based on provenance information. In addition, since KLG allows user to access security knowledge-bases, it is possible to provide actual and on time information about risk and security controls. Our proposed system implements a graphic representation of provenance using Open Provenance Model (OPM), and users are allowed to see graphically where and what kinds of data generate security conflicts.

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Election is an essential tool in democracy, and with the advancement of information technology nowadays, all aspects of election quality have also been greatly enhanced. Nevertheless, the quality from the trust aspect is still a distant goal especially in the developing world where the bond of trust between each stakeholder of the society is not as strong as in a developed country. Thus, it is also vital to understand the election from various aspects with the aim to improve it. This paper proposes a tool to understand the risk on an election result by approaching from a risk model of election result handling and simulating the model using a multi-agent simulation.

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A subdivision of a rectangle into rectangular faces with horizontal and vertical line segments is called a rectangular drawing or floorplan. Several encodings of rectangular drawings have been published; however, most of them deal with rectangular drawings without vertices of degree four. Recently, Saito and Nakano developed two compact encodings for general rectangular drawings, that is, which allows vertices of degree four. The two encodings respectively need 6f - 2n₄ + 6 bits and 5f -5 bits for rectangular drawings with f inner faces and n₄ degree four vertices. The best encoding of the two depends on the number of vertices of degree four, that is, the former is the better if 2n₄ > f+11; otherwise the latter is the better. In this paper, we propose a new encoding of general rectangular drawings with 5f - n₄ - 6 bits for f ≥ 2, which is the most compact regardless of n₄.

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Eigenvalues of graphs have been used for detecting non-subgraphs or non-supergraphs based on their interlacing property. However the detected subgraphs are often restricted to induced subgraphs or trees due to their matrix representations. We consider five matrix representations of a graph, which can be used to detect general non-subgraphs or non-supergraphs, and compare them experimentally.

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We discuss a scheme for hierarchical matrices with adaptive cross approximation on symmetric multiprocessing clusters. We propose a set of parallel algorithms that are applicable to hierarchical matrices. The proposed algorithms are implemented using the flat-MPIand hybrid MPI+OpenMP programming models. The performance of these implementations is evaluated using an electric field analysis computed on two symmetric multiprocessing cluster systems. Although the flat-MPI version gives better parallel scalability when constructing hierarchical matrices, the speed-up reaches a limit in the hierarchical matrix-vector multiplication. We succeeded in developing a hybrid MPI+OpenMP version to improve the parallel scalability. In numerical experiments, the hybrid version exhibits a better parallel speed-up for the hierarchical matrix-vector multiplication up to 256 cores.

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Wearable computing technologies are attracting a great deal of attention on context-aware systems. They recognize user context by using wearable sensors. Though conventional context-aware systems use accelerometers or microphones, the former requires wearing many sensors and a storage such as PC for data storing, and the latter cannot recognize complex user motions. In this paper, we propose an activity and context recognition method where the user carries a neck-worn receiver comprising a microphone, and small speakers on his/her wrists that generate ultrasounds. The system recognizes gestures on the basis of the volume of the received sound and the Doppler effect. The former indicates the distance between the neck and wrists, and the latter indicates the speed of motions. We combine the gesture recognition by using ultrasound and conventional MFCC-based environmental-context recognition to recognize complex contexts from the recorded sound. Thus, our approach substitutes the wired or wireless communication typically required in body area motion sensing networks by ultrasounds. Our system also recognizes the place where the user is in and the people who are near the user by ID signals generated from speakers placed in rooms and on people. The strength of the approach is that, for offline recognition, a simple audio recorder can be used for the receiver. Contexts are embedded in the recorded sound all together, and this recorded sound creates a sound-based life log with context information. We evaluate the approach on nine gestures/activities with 10 users. Evaluation results confirmed that when there was no environmental sound generated from other people, the recognition rate was 86.6% on average. When there was environmental sound generated from other people, we compare an approach that selects used feature values depending on a situation against standard approach, which uses feature value of ultrasound and environmental sound. Results for the proposed approach are 64.3%, for the standard approach are 57.3%.

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Towards the improvement for service provision through portable devices which have limited resources, we propose a new design of energy-consumption-aware evolutional agent system. In the proposed design, platform specific parameters of local resources are taken into account to calculate the energy continuance index (ECI) of portable devices for controlling service provision in order to reduce power consumption of the portable platforms. Furthermore, we implement a multimedia communication system based on the proposal in order to evaluate its effectiveness. Results from the comparison with a conventional design show that the proposal is able to provide adequate services without affecting user experiences.

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Recent recommender systems have achieved high precision in recommending favorite items to users. However, it has been reported that user satisfaction does not necessarily increase even when a recommender system recommends items high precision. User satisfaction is considered to be influenced by many factors. Among these factors, we focus in particular on user intervention. User intervention is a user control over a recommender system. We provide three hypotheses: i) user intervention in the recommendation process itself improves the user satisfaction, ii) user intervention improves the user satisfaction when the intervention is reflected in the recommendation results, and iii) the degree of improvement in user satisfaction differs among the types of user interventions applied. In this study, we conducted a user experiment using several kinds of interventions, and clarify the relationship between user intervention and user satisfaction.

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Several different methods for impulse noise removal in image sequences have been proposed. However, all of them are not successful in removing high density of impulse noise. Hence, this paper proposes a filtering method for reducing high density impulse noise in the image sequences. We use three windows with size 3 × 3 to obtain a new window with similar size. Three windows are taken from the next-frame, current frames and previous frames. The recursive window is applied in the current frames. The filtering process uses decision-based method. Meanwhile, a pixel for replacing the noisy pixel is calculated from a new window based on weighting method. Our experimental results show that the proposed method can not only reduce the high impulse noise in image sequences well, but also preserve more details and textures.

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Researchers have found that about 70% of information systems (IS) development projects in Japan have failed, thus increasing the demand for solutions that will increase expected project success rates. In this study, we seek to explore such a solution by identifying factors that affect the degree to which Japanese IS development projects succeed or fail. We accomplish this by using an Internet-based questionnaire and statistical analysis. The questionnaire, which was primarily comprised of questions related to CMMI, yielded responses from 650 project managers who work for Japanese IT vendors. Multivariate analyses and structure equation modeling techniques demonstrated that seven factors, “Ordering Company's Skill and Requirement, ” “Project Planning, ” “Detailed Planning and Product Quality in Each Phase, ” “Project Monitoring and Control, ” “Change Requirement Management, ” “Skill and Teamwork of Project Members, ” and “Schedule Progress in Each Phase” influence project performance. Results also showed that these factors covary.

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