Kochi University of Technology Academic Resource Repository

田尻, 史弥

Japanese

レイリー散乱型光ファイバ分布センサを用いた温度分布測定 による CFRP 積層板の損傷検出

橋本, 大輔

マルチエージェントシステムを用いた荷物搬送問題における強化学習の行動特性の検証

岡本, 宝

海浜礫の特徴と漂砂の関係に関する実証的研究

陸井, 健太郎

水平二方向偏心を有する一本杭頭接合部に関する設計法の提案

大内　雅博

持続社会建設材料研究室　－二酸化炭素をコンクリート材料の高機能化と物質循環サイクル構築に活かす－

浜村　昌則

138
英国 UCL での研修を終えて
浜村　昌則
（受領日：2024 年 5 月 31 日）
高知工科大学情報学群
〒 782-8502　高知県香美市土佐山田町宮ノ口 185 
E-mail: hamamura.masanori@kochi-tech.ac.jp
要約：本学の海外研修支援制度を利用して、英国ロンドンにある University College London
（UCL）に滞在してきた。支援制度への申請書の提出は 2020 年であったが、猛威をふるった新
型コロナウイルス感染症の影響により延期となっていた。当然、何か良い研究につなげたいと
いう思いを持ちながら共同研究を進めていたところ、予想を遥かに超えるアイデアに出会うこ
とができた。未発表につきこの研究の狙いまでを述べる。
1. はじめに 
Darwazeh 教 授 の い る 英 国 University College 
London（UCL）で海外研修をさせていただくこと
ができた。Darwazeh 教授は、70 にも及ぶ情報通信
に関係する研究室を含む UCL 内の大きなグループ
のリーダーである。Darwazeh 教授ご自身は通信・
コネクテッドシステム研究所長である。Darwazeh
教授と私の関係は、情報通信の周波数利用効率を向
上させるほぼ同じ方法を、2003 年のほぼ同じ時期
に、独立に発表したことに始まる。内容が新しいも
のの場合には、論文のタイトルやキーワードなどか
らお互いの存在をすぐには見つけられないというよ
うなことはよくあることである。これはまさにそれ
で、当初はお互いのことを知ることはなかったが、
数年後に Darwazeh 教授の方が先に私の研究を見つ
けてくれて、論文を紹介するなどしてくれていた。
2011 年にトロント（カナダ）で開催された IEEE 
International Symposium on Personal, Indoor and 
Mobile Radio Communications（PIMRC）という大
きな国際会議で、また偶然に、同じセッションで発
表する機会に恵まれて初めてお会いすることができ
た。セッションチェアでもないのに、参加者に大き
な声で私のことや、我々の研究のことを紹介してく
れたのを思い出す。実はこの PIMRC という国際会
議はポスドク時代にお世話になった King’s College 
London（KCL）の Aghvami 教授の創設によるもの
である。偶然は続くものである。
2. 共同研究の開始
2.1 技術の共有
共同研究のスタートは、UCL の Darwazeh 教授と 
Newcastle 大学の Xu 博士、私の 3 名で、お互いが
持つ最近の技術を出し合い共有することから始め
た。Darwazeh 教授は、Spectrally efficient frequency 
division multiplexing（SEFDM）と呼ばれる多重化
方式の研究をワイヤレス通信、光通信での実用化、
標準化に向けて積極的に推進している。Xu博士は、
干渉のある受信信号から干渉を除去する復号方式で
多くの研究成果を挙げている新進気鋭の若手研究者
である。そこに利用できそうな私の技術は、
SEFDM に適用可能なプリコーディング方式で、自
由に信号のスペクトルを制御できる。これらの共有
で、セルラネットワークや WiFi での収容回線数の
大幅な増大が見込めると判断してそこから共同研究
を始めることになった。また、Xu 博士と Darwazeh
教授が最近発表した、非直交スペクトルを持ち、か
つ、ナイキスト波形とならない、機械学習に基づく
新しいスペクトルシェイピングが大変興味深く、そ
れを学ぶことを進めていた。sin x/x 型のスペクトル
139
が少し修正された形状のスペクトルを持つ新しい信
号が構成されるものであった。それ以外にも、ゆっ
たりとした時間のもと、興味のある文献に目を通す
余裕と時間を持てたのが幸せだったし、それが見事
に次に繋がった。
2.2 全く新しい通信技術の誕生
前節で述べた方向で共同研究を進めていたが、あ
るところでピタッと止まって方向転換することに
なった。全く新しい通信技術が誕生したのである。
現在のスマートフォンやオペレータの基地局、
WiFi、地上波放送、衛星通信などほぼ全ての送信
機に適用可能な技術である。
現在のほとんどの高速ワイヤレス通信ではデータ
の送信に直交周波数分割多重（orthogonal frequency-
division multiplexing: OFDM）という技術が使われて
いる。この技術は直交振幅変調（quadrature 
amplitude-modulation: QAM）が施されたサブキャ
リヤ Nc 個の並列伝送を実現する。l 番目の QAM 信
号（ l = 1, 2, ..., Nc）は、メッセージデータ bl(1) 及び
bl(2) に よ り 変 調 さ れ た 及 び
 の和である。ここで、fc は 1 番目
の QAM 信号のサブキャリヤ周波数、T0 は QAM 信
号及び OFDM 信号の信号長である。したがって、
OFDM 信号 s (t) は次のようになる。
 　
今、bl = bl(1) + jbl(2)、j = √- l 、
と置くと次式が得られる。
　　
ここで、x(t) = ℜ[z (t)]、y(t) = ℑ[z (t)]、ℜ[・] と ℑ[・]
はそれぞれ複素数の実部と虚部を表す。
OFDM 信号 s (t) を上式の形で表現できることが
分かれば、OFDM の送信機は、x(t) と y(t) を入力
として s (t) を出力するシステムと捉えることができ
る（図 1）。Nc が大きいと、x(t) と y(t) の振幅変動
が大きくなることが知られており、それによって送
信信号 s (t) の包絡線 の変動が大きくな
る。このことは、信号のピーク対平均電力比（peak-
to-average power ratio: PAPR）が大きいと言われ、
PAPR の大きな信号の送信にはたくさんの無駄な電
力消費が発生することが知られている。未発表のた
め、ここでこれより先の詳細は述べられないが、こ
のような PAPR の大きな信号を送信する際の無駄な
電力消費を大幅に抑える新しい方法が見つかったの
である。このたびの海外研修で得られた大きな成果
である。
しばらくはこの技術について Darwazeh 教授と共
同で研究を進めることになるであろう。本学の学生
にも研究を通して多くの楽しみを与えられるはずで
ある。Darwazeh 教授のところにはたくさんの装置
類が揃っているため、今後はそれらを利用させても
らうことになると思うし、UCL サイドから出てく
る成果も楽しみでならない。
3. 研修先について 
UCL は 1826 年にロンドンで最初に創設された大
学である。11 ある学部のひとつが工学部で、工学
部だけで 600 人以上のスタッフがいる。お世話に
なったのは、地下鉄 Euston Square 駅のすぐそばに
メインエントランスのある Bloomsbury キャンパス
である。入ってすぐに立派なメインライブラリがあ
り（図 2）、そのすぐ右奥に、現代の日本を作った
と言われることのある長州ファイブの記念碑がある
と聞いていたので行ってみたところ、確かにあっ
た。まだ鎖国中の江戸時代末期に密航という手段
図 1:  新型送信アーキテクチャの誕生（未発表のた
め、イメージ図）
140
で、日本人初の留学で学んだのが UCL、それから
150 周年の年につくられたとのことである。記念碑
には長州ファイブと、その二年後に薩摩藩から続い
た留学生らの 19 人の名が刻まれている。
～はるばると　こころつどいて　はなさかる～
と刻まれていた。
この付近は日本ガーデンと呼ばれることがある
ようで、ソメイヨシノも植えられていた（図 3）。
UCL は創設当初から人種や信仰の違いを超えて
入学を認めてきた歴史的背景がある。近くにいた
人々の母国はエジプト、スーダン、インドネシア、
サウジアラビア、タイ、ポルトガル、イタリア、中
国、レバノン、ブラジル、…、ひとりの日本人、…
現在でも学生も教員も誠に国際的であった。
フレミングは UCL の中の工学部の中の電気系学
科の初代教授のようである（図 4）。
Darwazeh 教授のところでお世話になって本当に
良かった。たくさんの成果を挙げておられて頭脳も
素晴らしいが人柄も素晴らしく、いくつになって
も、また、いくら忙しくても、学生や研究員たちと
の研究の打ち合わせを最優先にする姿勢に、大学の
教員、こうあるべきだと感動した。
4. おわりに
新型コロナウイルス感染症の影響により延期と
なっていた海外研修に行ってきた。予定通りであれ
ば一緒に研究できる博士課程の学生がいたのだが、
延期の間に卒業し、残念であった。
面倒なことに年度が変わり、海外研修を中止させ
られそうにもなったが、どうにか行ってこられた。
関係各位の支援に感謝する。新型の送信アーキテク
チャにたどり着いたのが大きな成果である。
図 2: メインライブラリ
図 3:  日本ガーデン、記念碑（写真中央手前の黒い
石碑）とソメイヨシノ
図 5:  Darwazeh 教授のお宅に招かれてホームパー
ティ（右から筆者と Darwazeh 教授）
（a）フレミング教授（b）フレミング管
図 4:  UCL 初代電気系教授のフレミングとフレミン
グ菅
141
Brief Report on Research Residency at University 
College London (UK)
Masanori Hamamura
(Received: May 31st, 2024) 
School of Informatics, Kochi University of Technology
185 Miyanokuchi, Tosayamada, Kami City, Kochi 782-8502, JAPAN
E-mail: hamamura.masanori@kochi-tech.ac.jp 
Abstract: This is a brief report on my stay at University College London (UCL) in the UK using the 
Overseas Research Support Program of Kochi University of Technology. The application for the support 
program was submitted in 2020, but was postponed due to the effects of the raging coronavirus 
pandemic. While carrying out collaborative research, we came across an idea that far exceeded our 
expectations. Although the results are yet to be published, I have only briefly explained the aim of this 
research in this report. 


英国UCLでの研修を終えて

漆原, 舞

複合タグノックインラインとノックアウトラインを 利⽤したゼブラフィッシュ Pax6a の解析

吉田, 翔真

MRI 脳画像からのCNN による年齢推定モデルの説明性

岩田　誠，門田　宏，繁桝　博昭，島根　大輔，竹田　昂典，竹田　真己，松崎　公紀，山中　麻央子，吉田　真一，渡邊　言也，王　瑞敏，中原　潔

脳コミュニケーション研究センター　－脳科学をめぐる学際研究の場を目指して－

Hani. S. ELBEHIRI, Ibrahim KORAT, Ahmed LETHY, Masa-yuki YAMAMOTO

The 8th International Symposium on Frontier Technology (ISFT) 
 
EVENTS DETECTABILITY IN NORTH AFRICA AND MIDDLE EAST BY THE 
INTERNATIONAL MONITORING SYSTEM INFRASOUND STATIONS 
  
Hani. S. ELBEHIRI
1,2
, Ibrahim KORAT
3
, Ahmed LETHY
2
, Masa-yuki YAMAMOTO
1
 
Kochi University of Technology
1
, Japan 
National Research Institute of Astronomy and Geophysics 
2
, Egypt 
Mansoura University
3
, Egypt 
 
 
ABSTRACT: The infrasound wave is a type of low-frequency wave (less than 20 Hz). Furthermore, it 
propagates for long distances through the atmospheric layers with a velocity of ~ 343 m/s at 20° C without 
considerable attenuation. The International Monitoring System (IMS) infrasound stations are established for 
monitoring nuclear explosions in the atmosphere. Nowadays, the IMS infrasound network contains 53 
certified stations out of 60 planned to be constructed. Data from seven IMS infrasound stations around Africa 
for a period between the 1st of January 2013 and the 21
th
 of April 2018 is used in this study to estimate the 
detectability of events around Africa and the Middle East with data availability of more than 99.2%. The 
Progressive Multichannel Cross-Correlation (PMCC) algorithm developed by the Commissariat à l'Energie 
Atomique (CEA) (French Atomic Energy Commission) is used with 11 frequency bands for the data 
processing. These bands start at an extremely low frequency of 0.07 Hz and end at 4 Hz. In addition, 
Statistical analysis for this period is produced for qualitative and quantitative description using the Dase Tool 
Kit (Détections Infrasons Valorisées Automatiquement) (DTK-DIVA) software. The stations show a clear 
difference in detection numbers between day and night hours as the detections in the day hours are less than 
the night at all stations except at the Germany I26DE station, which has no noticeable diurnal difference 
being attributed to climatic and meteorological factors as most of the stations have tropical and dry climates 
except for this station, which has a temperate oceanic climate. Additionally, there is a vital relationship 
between seasons and the number of detections, as infrasound waves are affected by climate change. 
  
KEYWORDS: Infrasound, Atmosphere, Detections 
  
1. INTRODUCTION  
  
Infrasound waves are a type of low-frequency sound 
waves that have frequencies lower than the bottom 
limit of human audibility with a range from 0.003 to 
20 Hz [1]. Its propagation is strongly dependent on 
the temperature and wind structure of the 
atmosphere [2]. It travels from its source through the  
atmosphere with ~343 m/s at 20° C [3, 4]. These 
waves can travel thousands of kilometers through the 
atmosphere without considerable attenuation. 
Infrasonic waves are produced by many natural and 
manufactured sources. Natural sources include 
volcanoes, meteorites, large earthquakes, 
thunderstorms, microbaroms, and avalanches. 
Manufactured sources include mining and chemical 
blasts, nuclear explosions, wind turbines, drones, 
helicopters, and rocket launches [5–7]. The IMS is a 
part of the Comprehensive Test Ban Treaty (CTBT) 
verification regime [8, 9]. The IMS stations with 
The 8th International Symposium on Frontier Technology (ISFT) 
their four categories; seismic, infrasound, 
hydro-acoustic, and radionuclide monitor the world 
for any nuclear explosion worldwide in the solid 
earth, atmosphere, and oceans. IMS infrasound 
stations are distributed to detect explosions in the 
atmosphere with a yield equivalent to 1 kiloton of 
TNT  by at least two stations [10]. Studying the 
infrasound station detectability requires analysis of 
data for a long time.   
 
1.1 Data Set and the Study Area 
Seven infrasound IMS stations surround the research 
area and are used to study the event's detectability in 
North Africa. These stations are I17CI, I19DJ, 
I26DE, I31KZ, I32KE, I43RU, and T48TN. The 
Cote d’Ivoire I17CI station is considered the farthest 
one, with a distance to the nearest study point of 
about 3200 km. This distance is not considered a 
long one because infrasound waves travel through 
continents without considerable attenuation. These 
stations could cover the northern part of Africa 
including the study area (latitudes ~20-40  ̊ N and 
longitudes ~20-40 ̊ E). The used data is from 1
st
 
January 2013 to 21
th
 April 2018 (five years, three 
months, and three weeks). Additionally, data 
availability statistics are generated to estimate the 
status of stations during the study period. Figure 1 
shows the data availability study. It showed that, 
during this period, the average data availability was 
very high as it attained 99.29%. Figure 2 shows the 
study area and the location of the stations. 
 
 
Figure 1 Data availability histogram. 
 
Figure 2 The study area (green rectangular) and the 
surrounding seven infrasound IMS stations. 
 
2. METHODOLOGY 
The PMCC algorithm is the base of the infrasound 
data processing method [11–13]. By supposing the 
spectral amplitude is A(f), the signal phase is 𝜑(f) in 
the Fourier transform )Equation 1( that represents 
the signal in the frequency domain instead of the 
time domain.  
 
𝑆(𝑡) =  ∫ 𝐴(𝑓)𝑒𝑖∅(𝑓)𝑑𝑓
∞
−∞
      (1) 
 
By supposing a plane wave that propagates 
through several sensors that are distributed as an 
array, the variation in amplitude and phase between 
two sensors in the array is considered the 
background noise. In the ideal state without any 
background noise at different sensors, Equations 2 
and 3 represent the detections of the signal by 
assuming three sensors in the array that have (i, j, 
and k) positions.   
 
The 8th International Symposium on Frontier Technology (ISFT) 
  𝐴j(f) = Ai(f)            (2)                                                            
  
     𝜑j(f) = 𝜑i(f) − 𝛩 (𝑟𝑗−𝑟𝑖)        (3)                                       
 
The vector of the sensor position is represented 
with 𝑟. By cross-correlation between two sensors in 
the array, the delay of wave arrival could be 
measured from the variation in the atmospheric 
pressure. The delay in wave arrival time between 
two sensors at positions i and j can be defined as ∆tij 
which represents the only difference between the 
data recorded by the two sensors[14]. This phase 
delay depends on three parameters; the sensor 
position 𝛩.(𝑟𝑗 −𝑟𝑖 ) , trace velocity and the wave 
incident azimuth. The delay in time value for the 
record between any two elements in the array ∆t can 
be calculated from Equation 4.   
 
(4) 
 
For the planner wave that propagates through 
elements i, j, and k of an array, the sum of the delays 
in wave detection between every two sensors should 
be zero in case of neglecting the background noise. 
This relation is the closure one which can be 
represented in Equation 5.  
 
∆𝑡ij + ∆𝑡jk + ∆𝑡ki = 0    (5) 
 
If background noise is present within the wave 
propagating through an array of elements the sum of 
delays between elements is not exactly zero and the 
accuracy of the cross-correlation operation decreases. 
The algorithm is progressively applied, and the 
consistency value is calculated from the following 
relation. 
 
 (6)           
 
 
Cn is the consistency value, n is the number of 
elements, and rijk is the sum of delays between 
elements i, j, and k belonging to the array (Rn). The 
consistency value is calculated firstly from the 
delays between the smallest sub-elements triangle. If 
the consistency value is below the given threshold, 
the detection is stated [15]. 
 
2.1 Detection Parameters 
The International Data Center (IDC) parameters with 
the eleven frequency bands are selected for 
processing the data. These bands start at an 
extremely low frequency of 0.07 Hz and end at 4 Hz. 
Each frequency band has a different window length 
with an overlap percentage value. A long window 
length with a high-overlap percentage is used with 
the low-frequency band. Infinite impulse response 
filters are used by the PMCC software fitted with 
Chebyshev filters of orders 2 and 3 and ripples 
varying between 0.005 to 0.1. These parameters 
contribute to the source classification and location. 
Table 1 has a brief description of all frequency 
bands. 
 
Table 1 Eleven frequency bands with the detection 
parameters. 
 
 
3. RESULTS 
The statistical analysis applied to the seven stations 
surrounding the study area gives the quantitative 
manner of their detections and an inverse qualitative 
The 8th International Symposium on Frontier Technology (ISFT) 
description of the atmospheric state as wind 
directions. 
 
3.1 Diurnal Variation 
Detectability study of the stations shows an obvious 
difference in number between day and night hours 
(day/night property). This property could be 
attributed to the influence of solar radiation which 
was also detected in an experiment in Norway[16]. 
Figure 3 shows a pie plot for all stations in this study 
summarizing the diurnal variations in detection 
numbers. 
 
 
Figure 3 Comparison between day and 
nightdetection percentages. 
 
The number of whole detections during day 
hours is lower compared with that during the night 
hours at all stations except Germany I26DE station 
which has no noticeable day/night variation. The 
stability in its detections might be argued to be 
climatic and meteorological factors as this station 
has a temperate oceanic climate, while most other 
stations have tropical and arid climates. Table 2 
summarizes the classification of the climate at each 
station according to the Köppen-Geiger climate 
classification system [17]. 
 
Table 2 Climatic classifications at all stations. 
 
 
3.2 Seasonal Variation and Source Classification 
The infrasound wave is affected by temperature and 
climatic changes; therefore, the detection numbers 
vary with different seasons. All stations showed a 
seasonal variation for various sources as shown in 
the following station I17CI. Initially, the detections 
at the study station are attributed to various sources 
such as thunderstorms and local events with 
frequencies up to 5 Hz from different back-azimuths. 
In addition to microbaroms detected from oceanic 
waves specifically the Atlantic Ocean. Some of these 
sources are detected seasonally and others 
continuously. Microbarom detections with low 
frequency ranging between 0.01 to 0.5 Hz had been 
analyzed to show seasonal variation in this station. 
Figure 4 shows seasonal variation in I17CI stations 
specifically for microbaroms. 
 
Microbarom detections are distributed in various 
azimuths representing wind direction; especially 
from the southeast between 105-140˚, from the south 
160-220˚, and the west extending to northwest 
230-350˚. These microbarom detections are from the 
The 8th International Symposium on Frontier Technology (ISFT) 
Atlantic Ocean surrounding the Côte d’Ivoire station, 
from northeast to south directions, and from the 
southeast at the Gulf of Guinea. In Figure 4, The 
detections between 105-140˚ show seasonal 
variations as they appear in summer from mid-May 
to the end of August. Additionally, detections from 
the south between azimuths 160-220˚ witness 
seasonal increase in the warm season; spring and 
summer months from mid-April to the end of 
September. On the other hand, in the dry-hot season; 
from mid-November to mid-May, witness the 
microbaroms detections that come from the west and 
the northwest (between 230-350˚). 
 
 
Figure 4 Scattering plot of detection showing the 
seasonal variation of microbaroms (I17CI station). 
 
The second set from 0.5 to 5 Hz is represented in 
Figure 5 which contains high-frequency detections 
from sources such as thunderstorms and local 
artificial sources that also show seasonal variation. 
Figure 5 shows three clusters. The first has 
continuous detections all over the year near azimuth 
between 80 to 120˚. The second cluster is around 
azimuth ~150˚ with two occurrence periods from 
June to October and from December to the end of 
February. Finally, the detections from the west and 
northwest with azimuths between 220 and 350˚ Also 
have two occurrence periods; between March and 
mid-June and September to end-November. Not only 
does I17CI contain seasonal variation for the events 
but also all stations.  
 
Figure 5 Scattering plot of detection showing 
seasonal variation detections with a frequency 
between 0.5 to 5 Hz (I17CI station). 
 
4. CONCLUSION 
In conclusion, detections at all stations have both 
diurnal and seasonal variability. They have a higher 
probability during night hours than during day hours. 
Day and night change in detectability is attributed to 
solar radiation taking into consideration the climate 
change in different stations. The infrasound 
detections are seasonally dependent with the same 
cycles per year for those with frequency content less 
than 0.5 Hz which are microbaroms, and also for the 
high-frequency ones in I17CI station. Not only does 
the I17CI station show seasonal variation for various 
sources, but also all stations in the region. 
 
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English

EVENTS DETECTABILITY IN NORTH AFRICA AND MIDDLE EAST BY THE INTERNATIONAL MONITORING SYSTEM INFRASOUND STATIONS

Kochi University of Technology

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レイリー散乱型光ファイバ分布センサを用いた温度分布測定による CFRP 積層板の損傷検出