Showing papers by "Future University Hakodate published in 2019"

Internet Memes, Media Frames, and the Conflicting Logics of Climate Change Discourse

Abstract: Media frames have been applied to news information for decades to influence the manner in which news is both delivered and interpreted. However, media frames have tended to focus on traditi...

Nonexistence of global solutions of wave equations with weak time-dependent damping and combined nonlinearity

Abstract: In our previous two works, we studied the blow-up and lifespan estimates for damped wave equations with a power nonlinearity of the solution or its derivative, with scattering damping independently. In this work, we are devoted to establishing a similar result for a combined nonlinearity. Comparing to the result of wave equation without damping, one can say that the scattering damping has no influence.

Nonexistence of global solutions of nonlinear wave equations with weak time-dependent damping related to Glassey’s conjecture

Abstract: This work is devoted to the nonexistence of global-in-time energy solutions of nonlinear wave equation of derivative type with weak time-dependent damping in the scattering and scale invariant range. By introducing some multipliers to absorb the damping term, we succeed in establishing the same upper bound of the lifespan for the scattering damping as the non-damped case, which is a part of so-called Glassey's conjecture on nonlinear wave equations. We also study an upper bound of the lifespan for the scale invariant damping with the same method.

Secure Communication in Non-Geostationary Orbit Satellite Systems: A Physical Layer Security Perspective

Abstract: Satellite communication systems serve as an indispensable component of wireless heterogeneous networks in 5G era for providing various critical civil and military applications. However, due to the broadcast nature and full accessibility of wireless medium, serious security threats exist from such systems. As an effort to address this issue, this paper, for the first time, investigates the secure communication in a non-geostationary orbit (NGSO) satellite system from a physical layer security perspective. Specifically, we focus on the downlink of an NGSO satellite which provides services to a fixed earth station and is wiretapped by a fixed eavesdropper. We first apply three types of orbiting models to characterize the movement state of the satellite. Based on the orbiting models, we then provide theoretical analysis for the secure communication performance of such a system. The expressions of two fundamental performance metrics, secrecy capacity and secrecy outage probability, are derived in a closed form for any system time. Finally, we conduct extensive simulations to validate our theoretical performance analysis and illustrate the security performance in a practical NGSO satellite communication system.

Analysis and Prediction of Student Emotions While Doing Programming Exercises.

Abstract: The modeling of student emotions has recently considerable interest in the field of intelligent tutoring systems. However, most approaches are applied in typical interaction models characterized by frequent communication or dialogue between the student and the tutoring model. In this paper, we analyze emotions while students are writing computer programs without any human or agent communication to induce displays of affect. We use a combination of features derived from typing logs, compilation logs, and a video of the students’ face while solving coding exercises and determine how they can be used to predict affect. We find that combining pose-based, face-based, and log-based features can train models that predict affect with good accuracy above chance levels and that certain features are discriminative in this task.

Developing an Accessible Evaluation Method of VR Cybersickness

Abstract: Despite its growing popularity, Virtual Reality (VR) has yet to make a significant impact in conventional education due to its high cost, unconvincing learning data, complexity of the technologies and, persistently, cybersickness. To alleviate this dilemma, it is necessary to develop a straightforward and reliable measurement of cybersickness for VR application developers and mainstream educators. The Empatica E4 wearable device and its eco-system were utilized to record Heart Rate Variability (HRV) and Electrodermal Activity (EDA) during customized computer-based and VR tasks with 16 participants. The metrics of S, NNMean, SDNN, RMSSD, and Poincare Plot in HRV data and SCR width in EDA data were found to be potential indicators of cybersickness. Further research aims to determine a specific cybersickness index.

Walking on Glass: Reconciling Experience and Expectation within Japan

Abstract: This article utilizes an autoethnographic story-telling perspective in which I situate myself as a critical participant observer. Through critiquing the “situatedness of the self and others...

Exploring Factors that Influence Connected Drivers to (Not) Use or Follow Recommended Optimal Routes

Abstract: Navigation applications are becoming ubiquitous in our daily navigation experiences. With the intention to circumnavigate congested roads, their route guidance always follows the basic assumption that drivers always want the fastest route. However, it is unclear how their recommendations are followed and what factors affect their adoption. We present the results of a semi-structured qualitative study with 17 drivers, mostly from the Philippines and Japan. We recorded their daily commutes and occasional trips, and inquired into their navigation practices, route choices and on-the-fly decision-making. We found that while drivers choose a recommended route in urgent situations, many still preferred to follow familiar routes. Drivers deviated because of a recommendation's use of unfamiliar roads, lack of local context, perceived driving unsuitability, and inconsistencies with realized navigation experiences. Our findings and implications emphasize their personalization needs, and how the right amount of algorithmic sophistication can encourage behavioral adaptation.

Strongly Secure and Efficient Range Queries in Cloud Databases under Multiple Keys

Abstract: Cloud database provides an advantageous platform for outsourcing of database service. To protect data confidentiality from an untrusted cloud, the original database is often encrypted and then uploaded to the cloud. However, in order to support functional queries, existing secure databases require users to encrypt their data under the same public/symmetric key, which restricts the usage scenarios since users do not really trust each other in practice. Imagine a scenario where a user uploaded his/her own encrypted data to the cloud database and another user wants to execute private range queries on this data. This scenario occurs in many cases of collaborative statistical analysis where the data provider and analyst are different entities. Then either the data provider must reveal its encryption key or the analyst must reveal the private queries. In this paper, we overcome this restriction for secure range queries by enabling query executions on the multi-key encryption data. We propose a secure cloud database supporting range queries under multiple keys, in which all users could preserve the confidentiality of their own different keys, and do not have to share them with each other. At a higher level, our system is constructed on a two-cloud architecture and a novel distributed two-trapdoor public key cryptosystem. We prove that the proposed scheme achieves the goal of a secure query without leaking data privacy, query privacy, and data access patterns. Finally, we use extensive experiments over a real-world dataset on a commercial cloud platform to verify the efficacy of our proposed scheme.

Exploring Factors that Influence Connected Drivers to (Not) Use or Follow Recommended Optimal Routes

Abstract: Navigation applications are becoming ubiquitous in our daily navigation experiences. With the intention to circumnavigate congested roads, their route guidance always follows the basic assumption that drivers always want the fastest route. However, it is unclear how their recommendations are followed and what factors affect their adoption. We present the results of a semi-structured qualitative study with 17 drivers, mostly from the Philippines and Japan. We recorded their daily commutes and occasional trips, and inquired into their navigation practices, route choices and on-the-fly decision-making. We found that while drivers choose a recommended route in urgent situations, many still preferred to follow familiar routes. Drivers deviated because of a recommendation's use of unfamiliar roads, lack of local context, perceived driving unsuitability, and inconsistencies with realized navigation experiences. Our findings and implications emphasize their personalization needs, and how the right amount of algorithmic sophistication can encourage behavioral adaptation.

Friendship-based cooperative jamming for secure communication in Poisson networks

Abstract: This paper investigates the physical layer security-based secure communication in a finite Poisson network with social friendships among nodes, for which a social friendship-based cooperative jamming scheme is proposed. The jamming scheme consists of a Local Friendship Circle (LFC) and a Long-range Friendship Annulus (LFA), where all legitimate nodes in the LFC serve as jammers, but the legitimate nodes in the LFA are selected as jammers through three location-based policies. To understand both the security and reliability performances of the proposed scheme, we first derive analytical expressions for the transmission outage probability and determine both the upper and lower bounds on the secrecy outage probability, given the basic Laplace transform of the sum interference at any location in the network. With the help of the tools from stochastic geometry, we then provide general expressions for the above Laplace transform under all path loss scenarios as well as closed-form Laplace transform results under two typical path loss cases, such that the overall outage performances of the proposed scheme can be depicted. Finally, we present extensive numerical results to validate our theoretical analysis and also to illustrate the impacts of the friendship-based cooperative jamming on the network performances.

Cohesive and anisotropic vascular endothelial cell motility driving angiogenic morphogenesis

Abstract: Vascular endothelial cells (ECs) in angiogenesis exhibit inhomogeneous collective migration called "cell mixing", in which cells change their relative positions by overtaking each other. However, how such complex EC dynamics lead to the formation of highly ordered branching structures remains largely unknown. To uncover hidden laws of integration driving angiogenic morphogenesis, we analyzed EC behaviors in an in vitro angiogenic sprouting assay using mouse aortic explants in combination with mathematical modeling. Time-lapse imaging of sprouts extended from EC sheets around tissue explants showed directional cohesive EC movements with frequent U-turns, which often coupled with tip cell overtaking. Imaging of isolated branches deprived of basal cell sheets revealed a requirement of a constant supply of immigrating cells for ECs to branch forward. Anisotropic attractive forces between neighboring cells passing each other were likely to underlie these EC motility patterns, as evidenced by an experimentally validated mathematical model. These results suggest that cohesive movements with anisotropic cell-to-cell interactions characterize the EC motility, which may drive branch elongation depending on a constant cell supply. The present findings provide novel insights into a cell motility-based understanding of angiogenic morphogenesis.

Zero-shot Domain Adaptation Based on Attribute Information

Abstract: In this paper, we propose a novel domain adaptation method that can be applied without target data. We consider the situation where domain shift is caused by a prior change of a specific factor and assume that we know how the prior changes between source and target domains. We call this factor an attribute, and reformulate the domain adaptation problem to utilize the attribute prior instead of target data. In our method, the source data are reweighted with the sample-wise weight estimated by the attribute prior and the data themselves so that they are useful in the target domain. We theoretically reveal that our method provides more precise estimation of sample-wise transferability than a straightforward attribute-based reweighting approach. Experimental results with both toy datasets and benchmark datasets show that our method can perform well, though it does not use any target data.

Sports Training System for Visualizing Bird's-Eye View from First-Person View

Abstract: In ball games, it is important that the players are able to estimate the position of the other players from a bird's-eye view based on the information obtained from their first-person view. We have developed a training system for improving this ability. The user wears a head-mounted display and can simulate ball games in 360° from the first-person view. The system allows the user to rearrange all players, and a ball from the bird's-eye view. The user can then track the other players from the first-person viewpoint and perform actions specific to the ball game such as passing, receiving a ball, and (if a defense player) following offense players.

A Chaotic Boltzmann Machine Working as a Reservoir and Its Analog VLSI Implementation

Abstract: Reservoir computing is attracting great interest because of its high computing ability especially for time-series prediction, despite its simple structure and learning scheme. This paper proposes a reservoir computing hardware model using a chaotic Boltzmann machine (CBM) as the reservoir, which can achieve complex motion in a dynamical system on a high-dimensional hypercube. The CBM uses analog nonlinear dynamics, unlike the stochastic operation of the original Boltzmann machine model. To utilize CBMs as a reservoir, chaotic operation must be suppressed, and the echo state property should be satisfied. We modify the CBM model for simpler analog complementary metal-oxide-semiconductor very-large-scale integration (CMOS VLSI) implementation, and propose its use as a reservoir by adding an external reference clock signal. We then verify its proper operation by numerical simulation. We also refine the CMOS VLSI circuit design based on the proposed modified CBM model to improve power consumption and calculation precision.

Chaotic dynamics as a mechanism of rapid transition of hippocampal local field activity between theta and non-theta states.

Abstract: We propose a dynamical model of the local hippocampal circuit realizing the transition between the theta and non-theta states. We model the interaction between hippocampal local rhythm generators and the external periodic input from the medial septum and diagonal band of Broca (MS-DBB). With our model, bifurcation of the nonlinear dynamics serves as a mechanism that realizes two distinctive oscillations in the hippocampus, where the amplitude of the oscillatory input from the MS-DBB works as a bifurcation parameter. We model the network of the hippocampal interneurons with a network of simple class 1 neuron models connected mutually with gap junctions. The model neurons exhibit highly synchronous periodic oscillations under the existence of an external force from the MS-DBB, just as the real hippocampus shows theta oscillation under the rhythmic input from the MS-DBB. The model shows diffusion-induced chaotic dynamics under an aperiodic MS-DBB activity, just as the large amplitude irregular activity appears following the disappearance of the rhythmicity of the MS-DBB neurons in the real brain. The model is consistent with both previous experimental findings reporting the existence of local rhythm generators in the hippocampus and the executive role of the MS-DBB in synchronizing theta oscillation in vivo. Our model also replicates the traveling waves of theta oscillations in two-dimensionally coupled networks.

Zero-shot Domain Adaptation Based on Attribute Information.

Abstract: In this paper, we propose a novel domain adaptation method that can be applied without target data. We consider the situation where domain shift is caused by a prior change of a specific factor and assume that we know how the prior changes between source and target domains. We call this factor an attribute, and reformulate the domain adaptation problem to utilize the attribute prior instead of target data. In our method, the source data are reweighted with the sample-wise weight estimated by the attribute prior and the data themselves so that they are useful in the target domain. We theoretically reveal that our method provides more precise estimation of sample-wise transferability than a straightforward attribute-based reweighting approach. Experimental results with both toy datasets and benchmark datasets show that our method can perform well, though it does not use any target data.

Robust contrastive learning and nonlinear ICA in the presence of outliers

Abstract: Nonlinear independent component analysis (ICA) is a general framework for unsupervised representation learning, and aimed at recovering the latent variables in data. Recent practical methods perform nonlinear ICA by solving a series of classification problems based on logistic regression. However, it is well-known that logistic regression is vulnerable to outliers, and thus the performance can be strongly weakened by outliers. In this paper, we first theoretically analyze nonlinear ICA models in the presence of outliers. Our analysis implies that estimation in nonlinear ICA can be seriously hampered when outliers exist on the tails of the (noncontaminated) target density, which happens in a typical case of contamination by outliers. We develop two robust nonlinear ICA methods based on the {\gamma}-divergence, which is a robust alternative to the KL-divergence in logistic regression. The proposed methods are shown to have desired robustness properties in the context of nonlinear ICA. We also experimentally demonstrate that the proposed methods are very robust and outperform existing methods in the presence of outliers. Finally, the proposed method is applied to ICA-based causal discovery and shown to find a plausible causal relationship on fMRI data.

End-to-End Physical Layer Authentication for Dual-Hop Wireless Networks

Abstract: End-to-end (E2E) physical layer authentication for multi-hop wireless networks is still not well-explored by now. Like one step forward in this direction, this paper focuses on the E2E physical layer authentication in a dual-hop wireless network with an untrusted relay and proposes a corresponding physical layer authentication scheme. The scheme fully utilizes the location-specific features of both channel amplitude and delay interval of cascaded channels and adopts the artificial jamming technique, so that it is not only resistant to the impersonate attack from an unauthorized transmitter but also resilient to the replay attack from the untrusted relay. Theoretical analysis is further conducted to derive the expressions for the probabilities of false alarm and missed detection, which are two fundamental metrics of authentication performance. Finally, the numerical and simulation results are provided to illustrate both the efficiency of these theoretical results and the E2E authentication performance of dual-hop wireless networks under the proposed scheme.

The Communication Supporting Robot based on “Humanitude” Concept for Dementia Patients

Abstract: It is important for dementia-care to communicate with patients. However, care staffs cannot have an enough time to communicate with them. There is one of the care methods for dementia person called “Humanitude”. The purpose of this study is a development of a communication robot based on “Humanitude” concept for dementia patients and their staffs. This robot may be able to reduce behavioral and psychological symptoms for dementia patients, and reduce mental fatigue for the care staffs. We developed the communication model and “conversation” function, which is the basis of communication, and carried out the dialogue experiment with dementia patients using the robot. As a result, we could not get an effective evaluation about burden reduction. However, we could get a good evaluation about “Humanitude” under some certain circumstances. Therefore, it was suggested the potentialities of “Humanitude” using the communication robot.

Integrated datasets of normalized brain with functional localization using intra-operative electrical stimulation.

Abstract: The purpose of this study was to transform brain mapping data into a digitized intra-operative MRI and integrated brain function dataset for predictive glioma surgery considering tumor resection volume, as well as the intra-operative and postoperative complication rates. Brain function data were transformed into digitized localizations on a normalized brain using a modified electric stimulus probe after brain mapping. This normalized brain image with functional information was then projected onto individual patient’s brain images including predictive brain function data. Log data were successfully acquired using a medical device integrated into intra-operative MR images, and digitized brain function was converted to a normalized brain data format in 13 cases. For the electrical stimulation positions in which patients showed speech arrest (SA), speech impairment (SI), motor and sensory responses during cortical mapping processes in awake craniotomy, the data were tagged, and the testing task and electric current for the stimulus were recorded. There were 13 SA, 7 SI, 8 motor and 4 sensory responses (32 responses) in total. After evaluation of transformation accuracy in 3 subjects, the first transformation from intra- to pre-operative MRI using non-rigid registration was calculated as 2.6 ± 1.5 and 2.1 ± 0.9 mm, examining neighboring sulci on the electro-stimulator position and the cortex surface near each tumor, respectively; the second transformation from pre-operative to normalized brain was 1.7 ± 0.8 and 1.4 ± 0.5 mm, respectively, representing acceptable accuracy. This image integration and transformation method for brain normalization should facilitate practical intra-operative brain mapping. In the future, this method may be helpful for pre-operatively or intra-operatively predicting brain function.

“Froome with His SKY Bodyguards, Layers of Armour”: The ‘Sport is War’ Conceptual Metaphor in Grand Tour Cycling Commentary:

Abstract: The incorporation of metaphors into everyday language use has formed the basis of scholarly investigation for decades Particular attention has been given to conceptual metaphors, which are seen as

Millimeter-sized belt-like pattern formation of actin filaments in solution by interacting with surface myosin in vitro

Abstract: The movements of single actin filaments along a myosin-fixed glass surface were observed under a conventional fluorescence microscope. Although random at a low concentration, moving directions of filaments were aligned by the presence of over 1.0 mg/mL of unlabeled filaments. We found that actin filaments when at the intermediate concentrations ranging from 0.1 to 1.0 mg/mL, formed winding belt-like patterns and moved in a two-directional manner along the belts. These patterns were spread over a millimeter range and found to have bulged on the glass in a three-dimensional manner. Filaments did not get closer than about 37.5 nm to each other within each belt-pattern. The average width and the curvature radius of the pattern did not apparently change even when the range of actin concentrations was between 0.05 and 1.0 mg/mL or the sliding velocity between 1.2 and 3.2 μm/sec. However, when the length of filaments was shortened by ultrasonic treatments or the addition of gelsolin molecules, the curvature radius became small from 100 to 60 μm. These results indicate that this belt-forming nature of actin filaments may be due to some inter-filament interactions.

A temporary communication system using DTN for improving power consumption of mobile terminals

Abstract: The power supply interruption and the destruction of communications infrastructure in the event of wide area disasters make it difficult to communicate urgent information such as disaster situation and safety information. DTN (Delay Tolerant Network), which is an infrastructure-less communication technique, is one of the solution methods. However DTN has a problem of power consumption in order to realize information communication in a wide area disaster. The evacuees are assumed to communicate with others by their own mobile terminals in the disaster-stricken areas. Since these terminals have limited electric power, it is preferable to use a communication method considering power usage efficiency. In this paper, we propose a disaster-time communication system using a message ferry method for exchanging and collecting disaster situation and safety information. Also, in order to improve the power usage efficiency of the network on the proposed system, we propose and evaluate a method to efficiently utilize electric power for communication by setting multistage threshold for power remaining.

Paragraph-based Faded Text Facilitates Reading Comprehension

Abstract: We propose a new text layout that facilitates reading comprehension. By sequentially fading out characters sentence-by-sentence from the beginning of each paragraph, we highlight the paragraph structure of the entire text and the relative positions of the sentences. To evaluate the effectiveness of the paragraph-based faded text in a reading comprehension, we measure the comprehension, eye movements, and recognition for both the proposed method and a conventional standard method. In the proposed method, rates of correct answers to text comprehension questions are improved. Moreover, the proposed method leads to slower reading speeds and better recognition rates for the first sentences of paragraphs, which are displayed in a relatively thicker mode. With the paragraph-based faded text, the reader is naturally facilitated to pay attention to the first sentence of each paragraph, suggesting that this reading style could result in a more accurate text comprehension.