List of Dissertation Abstract (Department of Information Environment)
NameSupervisor

Mao Qingxin

Yoshioka
Katsunari

Aoki Shunsuke

Matsui Kazumi

Title

Abstract

Analyzing Carpet Bombing DRDoS Carpet bombing-type DDoS attacks that attack a wide
address range instead of a single IP address have been
Attacks Observed by Honeypot
reported. In this paper, we proposed a new aggregation
algorithm for carpet bombing and tried to understandthe actual situation of carpet bombing. As a result of
the analysis, it was confirmed that the above-mentioned
aggregation algorithm significantly reduces the numberof attacks during the period when the number of attacks
is rapidly increasing according to the conventional
definition of attack events.
In this study, ab initio calculations were used to
Ab initio calculations to estimate
the strength of two-phase interface evaluate the ideal shear strength of the two-phaseinterface of carbon steel. The slip stress was obtainedin carbon steels
by differentiating the potential curve along a slip path.
Its maximum value is evaluated as the ideal shear
strength.The interface is considered as a major
locations of void occurrence in the continuum damage
mechanics. By evaluating the sliding strength at thisinterface, this study contributes to understanding ofelementary processes of the ductile failure, namely void
occurrence, growth and coalescence.

To meet the security requirements of IoT systems,
which are expected to become more complex in the
future, advanced cryptographies, such as aggregate
signatures, are being put to practical use. Aggregate
signatures are often constructed using complex
operations, such as pairing points on elliptic curves, andreducing the computational time for pairing and thecomputational costs, such as power consumption andmemory usage, are issues that need to be addressed to
become widespread. For this reason, we present animplementation of pairing on the BLS12-381 curve thatis suitable for resource-rich servers and resourcelimited IoT devices, respectively, for use in advanced
cryptographies such as aggregate signatures.
An investigation of question-answer As a pre-processing step in the automatic
summarization of the congressional minutes with thematching methods for automatic
aim of creating a "Congress Newsletter (議会だより)".
summarization in congressional
There has been a demand for converting theminutes.
congressional minutes in the form of a batch ofquestions and answers into a one-question-and-answer
format. In this paper, we split the batch of questions
and answers to obtain the questions and answers thatare the elements of the one-question-and-one answer
format. Furthermore, the proposed method, which
focuses on the difference in the accuracy of thesegmentation, shows an improvement in the conversion
accuracy. In addition, a comparative study was carriedout on the method of matching questions and answers
obtained by segmentation.

ANZAI RIKU

MATSUMOTO A Study on Aggregate Signature
TSUTOMU
System for IoT Using BLS12-381
Pairing

igarashi naoki

mori tatsunori

Ishige taiki

tomii takashi

DB design and application of load
leveling oriented smart grid
integrating PV and EVThis paper describes a database design and its
application for simulation evaluation of a new smart
grid that integrates solar power generation and electricvehicles (EVs).Renewable energies, including solar
power, are unstable.This makes it difficult to match
power demand to power generation.To address thisproblem, EVs equipped with high-capacity batteries are
expected to make effective use of solar-generated powerby matching power supply and demand througheffective charging and supplying of power.In addition,
it is possible to suppress fluctuations in net load (loadleveling).This matching of power supply and demandby controlling the charging and feeding of EVs is called
VGI (Vehicle Grid Integration).This study evaluates
the feasibility of VGI by collecting location-specificdata and using an originally designed database schema.
In particular, this paper evaluated the simulation ofload leveling at annual level, combining several types ofreal data with reasonable hypothetical data.As a result,it was confirmed that fluctuations in net load could be
suppressed for most days of the year except for a few
exceptional days.It was also confirmed that much of thedriving power for commuting for the EVs participatingin the VGI comes from solar power.

Ichino Takahiro Nagao
Tomoharu

Unsupervised Video Hashing using
Image Clustering

Inoue Takahiro

Analyzing Environment-Sensitive
Malware using Sandboxes that
Simulate File System of Real IoT
Devices

Yoshioka
Katsunari

In recent years, due to the huge amount of video
content, there has been a lot of research on similaritybased video retrieval. Many studies have been carriedout using unsupervised hashing methods, but they
suffer from the problem of incomplete viewpoint
dependence. In this paper, we propose a method for
unsupervised video hashing using global and local
features of the video. Experiments on a motion
recognition dataset show that the proposed method
improves the retrieval accuracy compared toconventional methods.
In dynamic analysis of IoT malware that targets specificdevices, it is difficult to analyze the original behavior of
malware because a single analysis environment cannot
reproduce the internal configurations of various IoT
devices.In this study, we perform dynamic analysis in
multiple sandboxes that simulate the internal
configurations of devices built from the file systemcomponents of various IoT devices and analyze thefactors that depend on the execution environment bycomparing the behavior of IoT malware under different
device environments.

Imoto Sakuya

Matsui Kazumi

FE2 Evaluation of the Effect ofDistance Between Adjacent Voids
on Ductile Damage

UEDA
TAKAHIRO

Yoshioka
Katsunari

An internet-wide view of connected
cars: Discovery and attackobservation of exposed automotive
devices

Various papers have pointed out that the distance
between micro voids affects the macroscopic damage
behavior of materials. In this study, multiscale analysis
is used to evaluate the effect of micro voids spacing on
macroscopic ductile failure. The macroscopic loading
conditions are transformed by the multiscale method.
By changing the macroscopic stress direction in FE2
simulations, evaluate the anisotropic responses inmacro-scale, which are caused by their microscopic
structure. In addition, the effects of micro-void
distances are also evaluated in their macroscopic failure
behaviors.
In recently, although cyber-attack targeting connectedcars become significant risks. Among their entry points,
On-Board Equipment (OBE) that is directly accessible
from the Internet can be an immediate target. In thisstudy, we proposed discovery method to find OBE,
investigated the potential cyber-attack risks against
these discovered devices, and implemented thehoneypots imitating these OBE to reveal the state ofcyber-attacks against it. We believe this result provides
a lower bound of the security risk of Internet-facing
vehicular devices.

OkawaYasuhiro

ShirakawashinichiSymbolic Regression Method with
Solution Update Based on Gradient
Information

Ota Koki

Nagao
Tomoharu

Event-based Anomaly Detection
using Asynchronous Sparse
Convolutional Neural Network

Symbolic regression (SR) is a problem in identifying afunction expression representing a relationship of given
input-output data and has several applications, such assystem identifications. Cartesian Genetic Programming(CGP) solves SR problems by updating the network
structure representing a mathematical function using
the mutation operation. This study introduces anefficient solution update method into CGP, which
exploits the gradient information of the evaluation
function with respect to the intermediate outputs of a
network structure.
Recently, research of automatically anomaly detection
from videos has been progressing, due to the spread ofsurveillance cameras and the improvement of video
processing technology. In order to detect anomalies,
motion information acquisition and backgroundremoval are necessary, resulting in a complex process.
Therefore, event cameras, which record only brightnesschanges, are gaining attention. In this paper, we
propose a lightweight event-based anomaly detection
method using asynchronous sparse convolutional neuralnetwork. Also, we apply the proposed method to adataset for action recognition and evaluate thecalculation efficiency and anomaly detection accuracy
to verify the effectiveness in the experiment.

Otsu Takaya

Noma Atsushi

Study about class and singularitiesof dual variety of projective
hypersurface of dimension 2 withisolated singularities by resolutionof gauss map

Onogi Hiromu

Mori Tatsunori

Generating summary sentences ofparliamentary proceedings
introducing evaluation of questionanswer dialogue relationships by
GAN

The purpose of this study is to clarify properties ofisolated singularities of surfaces, and for that focus ondegree and singularities of dual surface. The method is
resolution of singularities and resolution of gauss map,
and we consider relation between dual surface anddivisors on the nonsingular surface. Here, ADE
singularities are one of the simplest singularities of
surfaces so that resolution of ADE singularities is wellknown. But There is no previous research calculating
resolution of gauss map of ADE singularities.
Therefore, this study shows resolution of gauss map
ADE singularities as a concrete example.
There is a great demand for automatic summarizationof parliamentary proceedings. It is necessary
considering the correspondence between questions andanswers when summarizing, but an effective method
has not yet been established. We tested a new method
to train a T5-based generative summary model toconsider the correspondence between questions andanswers by using an adversarial generative network(GAN). We also introduced a new framework for theloss function of the generator and tried a novel methodthat uses the generated question summaries as input
when generating answer summaries. The summaries
generated by the proposed method obtained higher
accuracy than the ones of many existing models.
Furthermore, we believe that the "readability" of thegenerated summaries was improved as a result of
human evaluation.

Owada Takumi

Matsumoto
Tsutomu

Magnetic Attack on
ElectroMagnetic Relay and Its
Countermeasure

OkumuraHiroyuki

Nagao
Tomoharu

MIPCE: Generating Multiple
Patches Counterfactual-changing
Explanations for Time Series
Classification

Relays are used in many electrical and electronic
devices, including switches and sensors. Relays areincorporated into various systems, and a malfunction ofa relay can significantly impact the entire system. One
such relay is the electromagnetic relay, which switches
circuits open and closed by operating the contact
points with an electromagnet. Due to theircharacteristics, electromagnetic relays are easily
affected by magnetic fields. Therefore, an attacker canillegally connect the contacts and manipulate thesystem by applying a strong magnetic field to theelectromagnetic relay. We havedefined this attack as a magnetic attack and reported its
potential as a major threat. In this paper, we propose amethod for evaluating the resistance of systems
including electromagnetic relays, based on theevaluation of the resistance of electromagnetic relays
alone to magnetic attacks.
We propose Multiple Patches Counterfactual-changing
Explanations (MIPCE) for time series classification.
First, MIPCE obtains time series subsequences fromfeatures appearing in the FCN and divides the timeseries into patches. Then, it generates the process ofchange to the counterfactual in each patch. We
compared MIPCE with other counterfactual
explanation methods in terms of proximity, plausibility,
and substitutability, and confirmed that MIPCE
provides explanations that follow the data distribution
and capture the features that contribute toclassification. Furthermore, we confirmed that the
proposed method leads to users' understanding of
DNNs through user tests.

Onodera Keita

Matsumoto
Tsutomu

A Research on Instrumentation
Security of Object Detection
Sensors Using Near-infrared Light

Kaneko Yuto

Shikata Junji

Multi-Authority Attribute-Based
Signatures from Lattice

The system uses sensors to detect objects. To operate
the system safely, it is necessary to consider the securityof the sensors. One of the object detection sensors is aphotoelectric sensor that uses near-infrared light.
Photoelectric sensors are widely used because of theirsimple structure. Therefore, it is necessary to consider
the security of photoelectric sensors. In this paper, we
examine attacks on reflective and transmissive
photoelectric sensors and clarify the threats. Then, we
conduct an attack experiment on an actual device toconfirm the studied threats.
We construct Multi-Authority Attribute-Based
Signatures (MA-ABS) based on lattices. Our scheme isthe first scheme that does not use Non-Interactive Zero
Knowledge proof (NIZK) and is secure under thelearning with errors (LWE) assumption. The idea isbased on the technique of constructing MA-ABS from
Multi-Authority Attribute-Based Encryption (MAABE) by Okamoto and Takashima (PKC 2013) and weapply this technique to lattice-based MA-ABE of
Waters et al. (TCC 2022).

Kanoya Kosuke Okajima
Katsunori

Generating Stair Walking
Perception by Manipulating
Audiovisual Information in Virtual
Reality Space

Kanno Haru

Existence and of the time periodic
solution of the Navier-Stokes
equation with large boundary data
in a time dependent domain

Ushikoshi Erika

We have developed a VR walking system that generates
the sensation of stair walking by presenting visual
stimuli that consider the foot and head movements
during stair walking while walking on a level ground inreal space. We conducted experiments to evaluate thesensation of ascent, driving force, fatigue, instability,
and stair walking. The results showed that each of thesenses was perceived more strongly than with existing
methods under certain conditions. Furthermore, we
added auditory stimuli matched with visual stimuli. The
results showed the sense of ascent was found to beenhanced. When the auditory stimuli did not coincidewith the visual stimuli, the perceived sensation tended
to decrease.
The purpose of this article is to prove existence of time
periodic solution of big boudary data in a timedependent dmain. Okabe(2011) proved existence oftime periodic solution of big boudary data in a time
independent dmain by using generalized Helmholtz
decomposition in Kozono-Yanagisawa(2009). Our way
is similar to Okabe.

Kubo Ataru

Matsumoto
Tsutomu

A Study on Attack ResistantRanging System Using Two Typesof Sensors

Sakakibara
ryujiShirakawa
ShinichiLearning Excavator Operating
Model Using Reinforcement
Learning

Information from distance sensors is important for
automatic driving to recognize the environment. On
the other hand, various attacks have been reported tocause the distance sensor to output incorrect distancemeasurement results. Therefore, it is important tostudy countermeasures against these attacks. In thispaper, we propose a method to detect attacks bycombining the outputs from two types of distancesensors. We also evaluate the effectiveness of the
proposed method by simulating several attack patterns
using a driving dataset.
In recent years, the shortage of skilled operators in theconstruction industry has become a problem, andautomation of construction machine operation isrequired. In this study, we aim to obtain a model thatcan operate a hydraulic excavator as well as a skilled
operator by combining supervised learning andreinforcement learning. Evaluation experiments showthat the proposed method is effective for the task ofaerial plowing with a hydraulic excavator in a simulated
environment. We also discuss the application of thelearned model to an environment different from thetraining environment.

SATO KAICHI

Ozeki Kenta

Upper bounds for isolation numberof k-trees and their best possibility

A dominating set in a graph is a subset of vertices used
to locate efficiently evacuation sites. Isolating sets arein a trade-off relationship with dominating sets in termsof cost, distance, and so on, and the minimum size ofisolating sets is called the isolation number. In thisthesis, we extend the upper bound of the isolation
number for maximal outer plane graphs to k-trees andshow its best possibility.

Sameshima
Kaichi

Yoshioka
KatsunariObservation of Vulnerability
Exploits and Attack Infrastructureof IoT Malware by Dynamic
Analysis

In recent cyber-attacks where IoT devices are targeted,
it is important to know the actual activities of IoT
botnets, collections of malware-infected devices, inorder to take countermeasures. In this study, dynamic
analysis is used to perform a longitudinal analysis of thevulnerabilities exploited by IoT malware forpropagation. It also aims to analyze activity trends byobserving the instructions sent to IoT botnets by
Command & Control servers managed by attackers.

Shichiri suke

Tomii Takashi

Design and effective use of EV
energy lifelog schema based on
space-sampled road data

Shibata
Hirokazu

Matsui Kazumi

EXAMINATION OF BASIC
ISSUES FOR EXTREMELY LOW
MACH NUMBER FLOWSAROUND THREEDIMENTIONAL SQUARECYLINDER

In this study, we propose a spatial energy analysis
method based on the collection of electric vehicle (EV)energy life logs.The energy consumption of EVs varies
greatly depending on road conditions, such as roadgradient, and driving conditions, such as
acceleration/deceleration and speed range.Therefore,
there is a demand for estimating the energy
consumption of EVs and aggregating and visualizing it
for each location.In this paper, "segments" of a road
divided by a certain distance are used as aggregation
units, and the energy consumed at each point isclarified.This enables more precise analysis of driving
and roads, and is useful for decision-making supportand review of driving.
The atmosphere forms a density stratification with adensity gradient in the height direction due to theeffect of gravity. Incompressible flow simulation has
been used in conventional studies of urban wind flow,
and the effect of density stratification on wind flow has
not been clarified. The objective of this study is toevaluate the effect of density stratification by applying
compressible flow simulation to urban wind flow. In its
early stage, compressible flow simulations to flow
around a three-dimensional square cylinder in uniform
flow are carried out to identify technical issues.

Shimamori Eiki

Mori Tatsunori

Detection and Modification ofRephrasing Expressions to Improve
Readability in Japanese Speech
Text

Shoji Manato

Nagao
Tomoharu

Mixing Data Augmentation using
Unlabeled Data for Environmental
Sound Classification

Speech transcriptions sometimes include rephrasing,which can reduce readability and cause errors in
subsequent processing. Although it is useful tomechanically correct these rephrasing, no analysis of
the rephrasing for the purpose of mechanical correction
has been conducted, and no method for comprehensive
correction of rephrasing based on such an analysis has
been studied. In this study, we proposed and evaluateda method for detecting and correcting the rephrasingthat appears in Japanese spontaneous speechtranscriptions.
Many methods using deep learning have been proposed
for environmental sound classification, but the obstacleis that the annotation cost of environmental sound datais high and there are few labeled environmental sounddata. On the other hand, there are many unlabeledenvironmental sound data. In this study, we proposed adata expansion method that uses unlabeledenvironmental sound data to generate pseudo data. As aresult, we confirmed that the classification accuracy was
improved by adding the pseudo data using the
proposed method.

Sugano Yuki

Okajima
Katsunori

Sugiyama
ShingoMori Tatsunori

Formulation of visibility and display The purpose of this study is to clarify the effects oftexture of luminous charactersluminance information on visibility and display texture
through decorative panelsof transmissive characters emerging from panels
decorated with wood grain patterns, etc., and toformulate using correlated luminance information foreach evaluation.In the experiments, samples of actual
objects and displays were prepared to reproduce
transmissive characters that emerge from thedecoration. The experimental results show that theluminance characteristics, such as the luminance slopeof the edges of the transmitted light letters, affect thevisibility and the display texture.
Automated scoring of descriptive
Automatic scoring technology that uses deep learning
examination using deep learning
to learn scoring rules from human-scored answers hastaking account of part of basis forbeen studied as a means of reducing the burden ofscoring in answers
scoring descriptive examination. In this research, we
proposed a model that uses supervised attention tolearn what the grader paid attention to in the answer
texts, and to score the texts while identifying the basis
for scoring. Experimental results showed that theaccuracy of scoring was improved compared to a modelthat did not use supervised attention, indicating theusefulness of learning the basis for scoring in
automated scoring system.

Sugiyama
Hiroaki

YamadaTakahiro

Sekii FumiyaMori Tatsunori

Deformation Pattern Simulations of In this paper, out-of-plane deformation pattern
Notched Sheet in Out-of-Plane
simulations of notched sheet were presented. A method
Directions
to extract buckling points on equilibrium paths in which
reaction force vector change constantly, and to show
the possible existence of a bifurcation paths extending
from the buckling points is proposed. By using thismethod, various deformation patterns were analyzed for
an elastic sheet by tracing the bifurcation paths, and it
was shown that bifurcation paths do indeed exist.
Furthermore, by extracting the buckling points on theobtained bifurcation paths, it was shown that theswitching points and bifurcation points of bifurcation
paths can be distinguished.
Construction of Werewolf Agents
We are studying how to realize dialogue such as
Using Mental Space and Genetic
persuasion and deception (dialogues inducing change
Algorithms and Analysis ofof mind) in werewolf games. In this paper, weDialogues Inducing Change of
constructed an agent that introduces the concept ofMindmental space for clarify the thought process as an agent
to be guided by a genetic algorithm, and observed themental space of the agent during the game to analyze
the difference in the internal state of each speech
protocol.

Soeda Shunki

Yoshioka
Katsunari

Analyzing environment-sensitive
IoT malware with bare-metal IoT
devices

Takao Kyohei

Yoshioka
KatsunariManaging and Operating URL
Blocklist using Cyber Security
Intelligence via Web Access Log

Some IoT malware is known as persistent IoT malware,
which continues to infect devices permanently evenafter they are rebooted. Although the threat of such
persistent IoT malware has been increasing, the devices
that can be the target of persistent infection and theremoval methods in the case of persistent infection
have not been sufficiently verified. In this study, we
propose a method of detecting persistent infection
using a simple assessment program that mimics the
behavior of persistent malware, and verify the presenceor absence of persistent infection and removal methods
with bare-metal devices.
Blocklists of malicious URLs are widely used to prevent
users from reaching malicious Web sites. In this study,
we proposed a method for managing the blocklist using
VirusTotal, and we focused on maintaining URL
blocklists and evaluated their detection/management
results.As a result of the evaluation experiment,
compared to previous methods, we could reduce thenumber of inquiries to VirusTotal was less than half
compared to the case without management while
maintaining an accuracy of 90% or more of ourblocklist while suppressing false positives due to a flipin VirusTotal's judgment.

TAKAHASHIAtsukiNOMA Atsushi

Classification of plane curves withm-ple point by system ofmultiplicity sequences

Takahashi
Daiki

Nakamoto
Atsuhiro

2-Connected spanning subgraphsof circuit graphs

While it is well known that plane curves with 2-ple
point can be resolved into nonsingular curves by blowup, the number of blow up required to resolve curves
into nonsingular curves with m-ple point (m>=3) is notknown. In this study, I performed blow up on plane
curves with 3 and 4-ple point, respectively, andattempted to classify the curves by system ofmultiplicity sequences. As a result, it was found thatplane curves with 3 and 4-ple point are classified into 7
and 19 cases, respectively.
The Hamiltonian cycle problem is an important topic ingraph theory and has been the subject of many related
studies. It is known that any circuit graph with nvertices has a 2-connected spanning subgraph of which
the number of edges less than 4(n-1)/3. It is also
known that this value is best. In this thesis, we give acharacterization of circuit graphs with n vertices forwhich the number of edges of any 2-connectedspanning subgraph must be at least 4(n-1)/3.

Takeda Misaki

Okajima
Katsunori

Evaluation of Walking Space by
Immersive Human Flow Simulation
Considering

Tachibana
KazukiMatsumoto
Tsutomu

A Study on Remote PhysicalAttacks against IoT Systems

In this study, an impression evaluation experiment was
conducted under three different density conditions toinvestigate the effect of the presence of human flow on
the psychological evaluation of walking spaces withdifferent structures and interiors using an immersive
human flow simulation. As a result, it was found thatthe wider the aisle width, the more comfortable it is towalk and the more lively it seems, but in a space withfew people, the width of the aisle has no effect. It wasalso found that placing objects near the wall is more
comfortable for walking, but in low-density spaces,
placing objects in the center gives a better impression.
This result indicates that spatial evaluation can be
performed even in a virtual space, and is expected to befurther utilized in architectural design.
IoT systems use a variety of devices for a wide range ofapplications. The leakage of confidential information
due to attacks inside these devices has become aproblem. Even if internal threats are eliminated, there
are still external threats such as eavesdropping on
communications between devices. In this paper, we
examine two specific threats: a remote physical attack
inside the device of an IoT system, and a remotephysical attack outside the device, showing that they areserious threats.

TamuraSadamichi

Fujii Tomohiro

On the c-command constraint inJapanese Wh-questions: A rating
and modeling study

Toya Kotaro

Matsui Kazumi

Numerical Simulation of GTN
model by Block Newton method

It has been known that in Japanese, wh-phrases such as“dare” are dependent on the Q particle “ka” in acertain way; wh-Q dependencies are subject to what iscalled the c-command constraint. The current study
conducted an acceptability rating experiment toexamine whether Japanese speakers possess thegrammatical knowledge in question. The results showthat the condition violating the constraint was rated
significantly lower than those that do not. The study
also addresses N-gram a learning model for theconstraint. It is demonstrated that our trigram model isable to learn the constraint when it is provided with thetraining data informing what syntactic nodes arespanned by wh-Q dependencies in child-directedspeech.
The objective of this paper is to define a coupledproblem of the equilibrium equation, the yield
conditional equation, the damage variable evolution
equation, and hardening coefficient evolution equation
for the elasto-plastic damage problem using the GTN
model, and to apply a numerical method to them basedon the Block Newton method by simultaneously
linearizing them.

Nakayama
Tomoe

Okajima
Katsunori

Quantifying the effect of chewing
sounds on the evaluation and moodof cold confectionery

Nishihara
Kenta

Shirakawa
ShinichiAutomatic Berthing Control Using
Reinforcement Learning inEnvironment with Control
Uncertainty and Wind Disturbance

To quantify the influence of chewing sound of cold
confectionery on food evaluation and mood change,
experiments 1 and 2 were conducted to evaluate soundstimuli with increased or decreased frequency
components of chewing sound and artificial chewing
sound of created chocolate. As a result, it was shownthat the pleasant evaluation of the chewing sound, thefeeling of hardness, and the mood evaluation before
and after the stimulus presentation were changed byincreasing or decreasing a specific frequency band, andthat the two kinds of artificial chewing sounds created
could be substituted as the actual chewing sound of
chocolate. In addition, when the sound stimuli thatshowed those changes in Experiment 1 and 2 were
presented at the time of eating, it was examined
whether they had the same effect on food evaluationand mood change, and it became clear that the samechange occurred in the pleasant evaluation.
Automatic ship operation has attracted attention in the
shipping industry as a solution to maritime accidents
caused by human factors and the seafarers' shortage. In
this study, we use reinforcement learning to address
automatic berthing, a technology necessary for realizing
automatic ship operation. This study aims to obtain theberthing control law on a simulator where thedifficulties of control in a real environment, such as theinfluence of the topography and wind in a real port andthe accuracy of the operation of ships' actuators, arereproduced. In addition, we propose a learning method
to handle these difficulties and analyze the success rate
of berthing and the collision probability with obstaclesin the harbor due to the difference in wind direction.

Nojo Daigo

Tomii Takashi

Application of Visualization System
Using SQL-Like Manipulation
Language and Data Manipulation
Acceleration for Lifelog Analysis

Noguchi
MasashiShirakawa
ShinichiA Robust Domain Generalization
Method for Open-Set Recognition
in Domain Shift

We have proposed a system (PC)2DV (Parallel
Coordinates Plot Commutative Data Visualizer) thatcan visualize data consisting of multiple attributes using
PCP, and store and reproduce their states in a unique
SQL-like language representation. In this paper, we
attempt to support data manipulation for the purposeof lifelog analysis. First, we show the usefulness of(PC)2DV by using it to analyze electricity data. Timeseries data acquired on a daily basis is converted into
periodic data by PIVOT operation, and visualized using
PCP. This allows us to visualize the periodic
information in the life log data. Next, (PC)2DV speeds
up data manipulation for lifelog analysis by reducing
the number of data by GROUP BY aggregation. As averification, we quantitatively compare the rendering
time with conventional methods and show that(PC)2DV is capable of big data analysis.
In real-world applications, a machine learning model isrequired to handle an open-set recognition, where
unknown classes appear during the inference, in
addition to a domain shift, where the distribution ofdata differs between the training and inference stages.
Domain-Augmented Meta-Learning (DAML) is amethod to consider this situation, where both domain
shift and open set recognition occur, but it is expensive
to learn. This work comprehensively evaluates domain
generalization methods for open-set recognition indomain shift and shows that computationallyinexpensive domain generalization methods exhibit
comparable performance with DAML. In addition, we
attempt to improve their methods by introducing thetechniques used in DAML and report theirperformance.

Noma Takaya

YOSHIOKA
Katsunari

Who Left the Door Open? Analyzing Root Causes for Exposed
IoT Devices through Campus
Notification and Manufacturer
Survey-Recently, vulnerable services such as Telnet and FTP
running on many IoT devices have been exploited incyber attacks. In this study, we conducted a university
notification survey and interviews with device
manufacturers, and we conclude that the presence of
misconfigured devices was less driven by the humanerror of the owners and more by the choices of the
manufacturers.

Hasegawa
yuichishikata junji

Security Analysis of a Lattice-based
Fuzzy Signature Scheme

In this paper, we focus on a fuzzy signature scheme,
which is an effective technique that provides
authentication of systems based on both biometric
information and cryptographic schemes. In addition,
the current trend of research on cryptography isincreasing the demand for the post quantum
cryptography(PQC) due to the realization of aquantum computer in the future. The existing postquantum fuzzy signature scheme presented by
Kaafarani and Katsumata is based on the RLWE (RingLearning with Errors) assumption, but we modify thisscheme so that its security is based on the MLWE
(Module-Learning with Errors) assumption, which is a
generalization of the RLWE assumption, and thenprovide a rigorous security proof. Also we give formal
security definitions for digital signatures, which aresuitable for constructing fuzzy signatures, and set
parameters based on our security proof.

Hiraishi Chika

Katsunari
Yoshioka

Proposal for a URL block list
creation method using external
security services and web access
logs

HIROSE Yoichi

SHIRAKAWA
ShinichiAutomated Feature Construction
with Domain Knowledge Using
Language Models

Security services using URL blocklists are widely usedagainst malicious sites, but the creation of blocklists is
time-consuming and technically expensive. In thisstudy, we propose a method for creating a URL
blocklist using Web access logs and external security
services to protect users of an organization. The resultsof evaluation experiments show that the proposed
method is more effective than other security services inprotecting users.
Feature construction is effective in improving machinelearning, and its automation methods have beendeveloped. However, they do not consider domain
knowledge sufficiently, and their execution timedepends on the number of columns in tabular datasets
because they create candidate features exhaustively. In
this study, we propose a method that predicts featuresfrom meta-information in a dataset and aims to exploit
domain knowledge using a language model. The
experimental results show that the performance of the
proposed method is comparable to previous studies andthat the execution time does not almost no change with
the number of columns in tabular datasets.

Fukuda Ittetsu

Shirakawa
ShinichiRobust Focus Classification Modelfor Different Shooting
Environments in Bhas42 Cell
Transformation Assay

Matsubara
Kyosuke

Nagao
Tomoharu

Prediction of Arteriosclerosis Index
from Medical Examination Data
Based on Medical Knowledge

In the Bhas42 cell transformation assay (Bhas42 CTA),a method for evaluating the carcinogenicity of chemical
substances, experimenters stain cells exposed to the test
substance and need to identify regions of cancerous cell
populations, called focus, visually. Deep learning-based
judgment models have been developed to reduce theexperimenters' burden and realize objective judgments.
In this study, we construct a robust focus judgment
model against differences in shooting environments
between model training and operation phases byautomatically selecting and applying image preprocessing during the model operation phase.
CAVI, an index of arteriosclerosis, is difficult tomeasure due to the need for individuals to visit medical
institutions and the difficulty of testing depending on
the area of residence. In this paper, we propose amethod to predict CAVI from medical examination data
to enable routine acquisition of the arteriosclerosis
index. The proposed method uses quantile regression
to indicate the range and probability in a multistage
manner, leading to the user's next action. Appropriate
pre-processing of input variables improves theprediction performance of CAVI, and comparative
validation experiments of four methods confirm theeffectiveness of the proposed method.

Mishima
Shigemasa

YamadaTakahiro

NUMERICAL SIMULATION OF
PLASTIC DEFORMATION OF
GRANULES IN POWDERCOMPACTION

Mishima Yudai

Okajima
Katsunori

Influence of temporal changes invisual information of food on taste
perception

The rearrangement and plastic deformation of granulesthat appear during the molding process of ceramics may
affect the quality of the final product. Prediction of
mechanical behaviors in compression molding from asingle particle characteristic enables the appropriate
control of particle characteristics to improve productquality. In this work, we propose a numerical procedure
for compression molding by considering the plastic
deformation of granules. Numerical results show thatthe proposed procedure can simulate the decreased
gaps between particles due to plastic deformation.
The purpose of this study was to measure the effects ofvisual information of food on taste perception. Basedon psychophysical experiments, we examined theeffects of visual information on taste expectation offood, presentation time of visual information, andtemporal variation of visual information. The results
showed that the cross-modal effects of color and taste
information require prior expectations, and that these
expectations are larger the longer the presentation timeof color information is. It was also shown that visual
information input just before eating significantly affects
taste perception.

Yazaki
Hirofumi

Nishimura
Takashi

Fundamental problems in theenvelop in the plane

A family of straight lines may create a curve called anenvelope. This is a field where this curve has beenstudied for a long time. I consider four basic problems
about their envelopes in the plane: definition problem,
existence problem, representation problem, anduniqueness problem. Special attention is paid to thesituation when the Gauss map has a singularity andwhen it does not, since the situation is different.

Yamanishi
kouta

Shirakawa
Shinichi

Proposal of Neural Additive Models
with Feature Selection Using Prior
Information

Neural Additive Models (NAMs) exhibit excellent
interpretability and prediction accuracy, which are
effective for tasks requiring an explanation of the basis
for predictions, such as medical and legal applications.
Extensions of NAMs, such as methods taking into
account feature interactions and introducing a feature
selection mechanism, have also been proposed. In thisstudy, we propose to use feature importance given fromsuch as domain knowledge and sensing cost as priorinformation in NAM with a feature selection
mechanism.

WANG FUJUN

OKAJIMA
Katsunori

Haptic system for reproducing foodtactile felt by hand through cutlery

ZHANG ZIOUNAGAOTOMOHARU

Improving the Accuracy of Small
Object Detection in Drone Images
Using Super-Resolution

Aiming to simulate the tactile of food by hand throughcutlery. First, the texture characteristics of food wereobtained using a compression test machine. Next, thereal touch of the food was replicated by adjusting thevariables of the haptic device (Phantom). Then, basedon these data, multiple regression analysis was
performed and a model that can predict each haptic
variable was obtained. Results from the reproduction
evaluation experiment with two conditions (with andwithout visual stimulation), showed that the touch of
cutting and piercing food can be accurately reproduced,
and the influence of visual stimulation on touch wasdemonstrated.
In recent years, drone imagery has been increasingly
developed and applied in a variety of fields. However,
object detection using drone images is less accurate fordetecting small objects. For drone images with low
resolution, small objects have little pixel information sothat improving object detection methods alone is not
sufficient. In this study, we propose a method toimprove the accuracy of small object detection in drone
images by using superresolution. And experiments
using actual drone images confirmed the accuracy
improving.