Many methodologies and techniques, which solve various problems related to society, management and technology, are currently proposed. However, it is difficult to judge which technique should be selected for the target problem (the problem of technique selection), and to know the role sharing and the communication method in applying the technique to the project (the problem of technique operation).
In this paper, we focus on the language actions exchanged among the members of the problem-solving project, and clarify two conversation models - conversation for problem-definition (analytic type) and conversation for solution-generation (synthetic type). We also propose the network model for designing problem-solving process based on these conversation models, and show its effectiveness by some case studies.
We propose a schema matching method of transport service data in different schema from multiple data sources. Nowadays, open data about transport services are increasing. However, there are some challenges to use them, because they have complicated data structure such as deeply nested objects or linked small objects. And their disparate data structures make data mathcing more difficult. So we present a method to make match trasnport services data by exploit the data strucutre, terminology and domain knowledge. The proposed method gradually add linked objects to matching target in mathcing process to find corresponding attributes. Generally, wider matching target space raises false positive rate. So our proposed method caluculates similarity score of attributes taking into account reference relationships between linked objects. We experimentaly evaluate the method in real-world transport service data and comfirm the method can improve mathcing accuracy.
The physical unclonable functions (PUFs) have attracted attention to ensure the security of internet of things (IoT) devices. On the other hand, the threat of machine learning attacks is pointed out; therefore, the feed-forward arbiter (FFA) PUF has been proposed as the resistant PUF. This study proposes a new machine learning attack for the FFA PUF. The proposed method focuses on both power consumption generated during the operation and the selectable challenge, and a hybrid machine learning attack which combines them are introduced to predict the response of the FFA PUF. Experiments using a field programmable gate array evaluate the validity of the proposed method.
In this paper, we propose, verify and evaluate a method combining cross-layer method and bandwidth allocation to overcome the difficulty of flow control in a network with large bandwidth delay product. When the bandwidth delay product is large, there are problems with the convergence time, efficiency and stability of bandwidth utilization, fairness among traffics of different round-trip time. As a result of examining the conventional methods, we propose a novel method which can be realized as a functional addition to the existing TCP flow control with improvement in utilization efficiency, fairness, stability and convergence time. The method is compared with TCP Reno, FAST TCP, CUBIC, ECN and XCP by simulation, and is confirmed as having good characteristics.
This paper proposes a method to estimate the vascular age from the reflected photoplethysmogram (PPG) waveform. Mobile devices such as smartphones are rapidly penetrating daily life, and health management using them is expected. This paper deals with a method of estimating the vascular age using a reflective PPG sensor attached to a mobile device. In the proposed method, contour lines are drawn on the PPG and the derivative PPG waveform, and features are extracted from them. Since many features are extracted, the influences of multicollinearity are concerned. Therefore, partial least squares regression which is not affected by multicollinearity was used as an estimation method. We compared the estimation accuracy with the conventional method using height ratio feature.
For monitoring the safety of divers, we propose an underwater electromyogram (EMG) sensor that is incorporated into a wetsuit. The sensor has cavities in front of the EMG electrodes. Except for parts of the cavities in contact with human skin, the sensor is covered with chloroprene rubber sponge, which is used to make wetsuits. When using our EMG sensor under water, the cavities of the sensor are filled with liquid, and, by pressing the sensor to the skin, the liquid inside the cavities are physically isolated from the liquid outside the sensor. We fabricated our sensor and conducted EMG-signal measurements in seawater and freshwater. We found that, in the case of seawater, the EMG signals were observed by completely isolating the liquid in the cavities. In the case of freshwater, the EMG signals were observed even when in incomplete isolation of liquid. We also calculated EMG signals from an equivalent circuit model of our sensor. We found the same tendency as in the measurement results.
An accelerated alternating direction method of multipliers (ADMM) has been proposed as an effective method for solving DC optimal power flow (DC-OPF) problems. However, the accelerated ADMM partially needs centralized calculation to accelerate a distributed ADMM algorithm, and therefore, loses some advantages of distributed algorithms such as high reliability against failure. To cope with this difficulty, this paper proposes a fully-distributed accelerated ADMM by combining the so-called push-sum algorithm, and illustrates its effectiveness through simulation results of DC-OPF problems.
This paper proposes a method to generate a 2.5D map for an indoor environment with floors including non-horizontal partial areas by plotting the range data measured by a wheeled robot having two 2D range finders and a 3D gyroscope. For precise map generation, this method estimates the robot's 3D orientation by using not only the gyroscope but also the 2.5D map that are still being generated, and prevents the robot from adding erroneous floor concavities and convexities to the map by using the following two techniques. One technique detects and corrects the erroneous measurement of basic horizontal floors with a distance threshold related to the standard error of floor measurement. The other technique determines a 3D orientation estimation parameter to reduce the bad influence of erroneous floor concavities and convexities on the map. In experimental tests, it is verified that the 2.5D map generated by this method can be used for floor detection from range data captured by the robot on a small downhill slope.
To avoid low data-access performance through wide area network (WAN) from clients at remote offices to a cloud storage at a data center, we proposed a cloud-storage cache, called “cloud on-ramp” (CoR). Because the CoR is located at the remote office and connected to the clients through local area network (LAN), it can improve access performance from applications. However, a bulk copy that synchronizes data from the CoR to the cloud storage causes performance overhead. Especially, the more periodical bulk copies occur, due to ensure that distributed users can share more fresh data through the cloud storage, the more snapshots need to be taken, which keep data consistency but cause performance degradation for the applications. To ensure that the applications have reliable access to data even in the case of the periodical bulk copies, we propose a snapshot method called “intermittent snapshot” and a remote data synchronization method based on it. Execution timing of both the bulk copy and the snapshot completely synchronize, and the snapshot terminates after the bulk copy completion during the remaining period of a periodical bulk copy window, in which the application access performance ensures. In addition, we evaluate the remote data synchronization based on the intermittent snapshot from the perspective of an implementation design. We formalize the method by utilizing a stochastic Petri-net model, and determine a proper size of bulk copy window that optimize both synchronization delay and application access performance through Petri-net simulation. We also evaluate its data access performance improvement in comparison with a conventional method and a limit performance of the method.
We fabricated an electrocardiogram (ECG) electrode with a novel isolation structure to detect heartbeats of divers in seawater. The electrodes placed at the center-left and right of chest measured ECG of a test subject at rest in a bathtub filled with seawater. We demonstrated that R waves, which are necessary for monitoring heartbeats, were detectable in the ECG signals at least for an hour, although the R wave amplitude decayed to two-third with time.