Comparison of peripersonal space in front and rear spaces

The space immediately around the body, referred to as the peripersonal space (PPS), plays a crucial role in interactions with external objects and in avoiding unsafe situations. This study aimed to investigate whether the size of the PPS changes depending on direction, with a particular focus on the disparity between the front and rear spaces. A vibrotactile stimulus was presented to measure PPS while a task-irrelevant auditory stimulus (probe) approached the participant. In addition, to evaluate the effect of the probe, a baseline condition was used in which only tactile stimuli were presented. The results showed that the auditory facilitation effect of the tactile stimulus was greater in the rear condition than in the front condition. Conversely, the performance on tasks related to auditory distance perception and sound speed estimation did not differ between the two directions, indicating that the difference in the auditory facilitation effect between directions cannot be explained by these factors. These findings indicate that the strength of audio-tactile integration is greater in the rear space compared to the front space, suggesting that the representation of the PPS differed between the front and rear spaces.journal articl

The Change of Infection Prevention and Psychosomatic States ofStudents at Muroran Institute of Technology during COVID-19 -A Latent Class Analysis-

The behavior of Infection Prevention and Psychosomatic state of Students at Muroran Institute of Technology during Covid-19 period between 2020 and 2023 are estimated by general statistical analysis and a latent class analysis. The results indicate that there is no clear difference by years, however students were shown to be sensitive to the policies of the university and the government, and to react as best they could in their own lifestyles. Stress might divide their way to react.departmental bulletin pape

汚泥処理設備における機械学習を活用した自動制御に関する研究

室蘭工業大学Muroran Institute of Technology博士（工学）わが国の下水道事業は，財政面および運転の体制面において様々な問題を抱えている．特に職員数の問題に対して，5年後にベテランオペレータの大量退職が予想されており，現在の運転体制を維持できない恐れがある．この問題に対して，国土交通省は下水道に関するAIを活用した運転操作デジタルトランスフォーメーション検討会を行うなど，運転操作の自動化や効率化に向けた取り組みを積極的に推進している． 本研究では，機械学習やディープラーニングを活用し，汚泥処理設備における自動運転を目指す．具体的には，これまで経験を積んだオペレータによる運転操作を完全自動化し，目標値に対する制御性能および資源使用量の効率化の面から評価を行った．対象とする設備は，脱水設備と焼却設備が一体となった創エネルギー型脱水焼却システムであり，それぞれの設備において手動介入が必要な運転箇所の自動化および効率化を試みた． 脱水設備では，適切なフロック状態を維持するため，オペレータがフロックを目視確認することでポリマー注入量を調整し，設備を安定化させていた．これに対して，画像からフロック状態を推定し，最適なポリマー注入量を制御するシステムの開発を行った．具体的には，セマンティックセグメンテーションを用いてフロック間の間隙面積を算出し，間隙面積をフロック状態の推定値とした．この間隙面積を使用したポリマー注入量の自動制御を実現し，オペレータの運転実績と比較したところ，制御性能およびユーティリティ使用の効率性の両面において優れていることを明らかにした． 一方，焼却設備は焼却炉内温度の安定化を目指した手動運転が行われている．炉内温度の安定化は，脱水汚泥の搬送・滞留時間を考慮した上で，焼却炉に適した含水率となるよう脱水機を運転する必要がある．これに対して，焼却炉の燃焼傾向を予測するモデル予測制御と脱水汚泥の含水率を機械学習によって予測し，脱水機を制御するシステムを組み合わせたカスケード型制御を構築した．本カスケード型制御は，炉内温度の傾向を予測するとともに燃焼に適した含水率を出力し，出力された含水率となるように脱水機の制御を行うシステムとなっている．ここでは有用性を検証するため，オペレータの運転実績と比較 を行った．結果として，制御性能の面とユーティリティの使用面において優れていることを明らかにしたOur country’s sewage works are facing various problems in terms of financial and operational management. Particularly regarding the problem of operator numbers, a mass retirement of veteran operators is anticipated in five years, raising concerns about the ability to maintain the current operational system. Particularly regarding the problem of operator numbers, a mass retirement of veteran operators is anticipated in five years, raising concerns about the ability to maintain the current operational structure. For this problem, the Ministry of Land, Infrastructure, Transport and Tourism is actively promoting initiatives aimed at automating and streamlining operational management, including conducting a study group on digital transformation utilizing AI related to sewage plant. In this study, we aim to achieve automated operation of sludge treatment plants by utilizing machine learning and deep learning techniques. Specifically, the study evaluated the full automation of operational management previously performed by experienced operators, assessing control performance against set values and the efficiency of resource usage. The experimental plant is an innovative energy-generating sludge treatment system that combines dewatering and incineration process. Efforts were made to automate and optimize the points that require manual operation in each piece of process. In the dewatering process, to maintain an appropriate floc condition, operators adjusted the polymer dosage based on visual confirmation of the floc, thereby stabilizing the plant. We developed a system that estimates the floc condition from images and controls the optimal polymer dosage. Specifically, we calculated the area of gap between flocs using semantic segmentation and constructed an automated polymer dosing system based on the gap area. When compared to manual operation by operators, this system achieved superior results in terms of control performance and efficiency of utility usage. On the other hand, manual operation of the incineration process is conducted with the aim of stabilizing the internal temperature of the incinerator. To stabilize the internal temperature of the incinerator, the dewatering process must be operated to achieve a moisture content appropriate for the incinerator, taking into account the transport and retention time of the dewatered sludge. We constructed a cascaded control system that combines model predictive control for predicting the combustion tendencies of the incinerator with a system that controls the dewatering equipment based on the moisture content of the dewatered sludge predicted by machine learning. The system was compared to manual operation by the operator and was superior in terms of control performance and utility usage.doctoral thesi

Reversal Structure in the New Testament ‘Epistle to the Ephesians’: Verification Based on Murai’s Chiastic Structure

本稿では、新約聖書の「エペソ人への手紙」の分析を、裏返し構造の特徴と照合する観点からおこなった。裏返し構造は、異郷訪問譚における構造上の「共通の約束」であるとされてきた一方で、聖書テキストにおいては、異郷訪問譚の形式ではないにもかかわらず、当該構造がみとめられる事例があることが報告されている。本稿の目的は、聖書テキストに裏返し構造がみいだされることの蓋然性を検証するところにある。本稿の知見によれば、「エペソ人への手紙」は裏返し構造により構成されている。journal articl

Inventory of Polynesian Prepositions

journal articl

Usage of Polynesian words for “water”

多くのポリネシア諸語においては、「淡水」と「海水」の区別が語彙的に明確な形でなされているか、或いは、淡水と海水の明確に区別せず一般的に水を表す語を用いる言語でも、別途専ら「海水」を表す語が存在するという事例が多くみられた。これには淡水と海水の区別の重要性が反映しているものと考えられる。水以外の様々な水状の液体については、概して、甘いものは淡水又は水（一般）の下位区分として、塩気のあるものは海水の下位区分として分類される傾向がみられた。また、薬及び身体から出される液体については淡水又は水（一般）の下位区分として分類される傾向がみられた。journal articl

EVALUATION OF MISSING PROCESSING AND INFERENCE FOR PREDICTION OF WATER LEVEL USING SPARSE MODELING WITH HIGH MISSING RATE

本論文では，欠測値を含むデータセットから直接学習可能な欠測対応スパースモデリング（HMLasso）による水位推論を提案し，その有効性を検証した．河川情報で生じる観測所の未観測，観測エラーなどによる欠測への対応手法として，HMLassoによる欠測処理の有用性を検証するため，令和4年8月に出水事例が報告された最上川を対象に，従来法と比較した．さらに，学習データの欠測率を最大50%まで人為的に増加させ評価した．その結果，HMLassoモデルはNash-Sutcliffe係数で，実測値で学習した場合で0.876に対し，50%欠測では0.842と，欠測率による性能低下が少ないとわかった．In this paper, we propose a inference model for prediction of water level using the HMLasso (least absolute shrinkage and selection operator with high missing rate) algorithm. The HMLasso algorithm enables the learning of models directly from data sets that contain missing values. In the collection of river data, there are several factors that can induce missing data. These factors encompass the closure of telemeter, their installation, and observation errors. We conducted a comparative analysis between conventional method and the HMLasso model. The analysis was carried out on the Mogami River during a flooding event in August 2022. To facilitate this comparison, we artificially increased the missing data rate up to a maximum of 50% and performed multiple analyses. As a result, when trained using actual values, the Nash-Sutcliffe coefficient was 0.876. However, even with a 50% data missingness rate, the coefficient reduced only marginally to 0.842. This results that the HMlasso model's performance degradation due to missingness rate is relatively minimal.journal articl

Improvement of Channel Capacity of MIMO Communication Using Yagi-Uda Planar Antennas with a Propagation Path through a PVC Pipe Wall

This study investigates the improvement of the channel ca- pacity of 5-GHz-band multiple-input multiple-output (MIMO) communica- tion using microwave-guided modes propagating along a polyvinyl chloride (PVC) pipe wall for a buried pipe inspection robot. We design a planar Yagi–Uda antenna to reduce transmission losses in communication with PVC pipe walls as propagation paths. Coupling efficiency between the an- tenna and a PVC pipe is improved by attaching a PVC adapter with the same curvature as the PVC pipe’s inner wall to the Yagi–Uda antenna to eliminate any gap between the antenna and the inner wall of the PVC pipe. The use of a planar Yagi–Uda antenna with a PVC adaptor decreases the transmis- sion loss of a 5-GHz-band microwave signal propagating along a 1-m-lomg straight PVC pipe wall by 7 dB compared to a dipole antenna. The channel capacity of a 2 × 2 MIMO system using planar Yagi–Uda antennas is more than twice that of the system using dipole antennas.journal articl

A Study of Hybrid Adaptive Evolutionary Algorithm for Multi-objective Optimization

室蘭工業大学Muroran Institute of Technology博士（工学）進化アルゴリズムは，生物の進化過程からインスパイアを得ており，交叉，変異戦略，自然選択といった進化操作により最適化を実現している。進化計算は，その高い汎用性および頑健性から，伝統的な数学的計画に比べて幅広い問題に対処することができるという特徴を持つ。特に最近では，進化計算における多点探索という特徴を活かした多目的最適化問題への応用研究が大きな注目を集めている。本研究は，多目的最適化のための効果的な進化計算手法として，新規個体生成のためのメカニズムとしてCX（Cross-over）およびED（Estimation of distribution）戦略を組み合わせた新たな手法を開発し，その有用性を検証した。 多目的最適化は，単目的最適化よりも複雑であるため，探索性能を向上させるためには，より体系的かつ適応的な手法が必要となる。本研究では，代表的な多目的最適化のための進化計算手法であるMOEA/D（Multi-Objective Evolutionary Algorithm Based on Decomposition）フレームワークに焦点を当て，そのフレームワークに新たなメカニズムを導入することによる性能改善を試みた。一般的に，進化計算における新規個体生成では，幅広い範囲を対象とする探索と局所的な範囲を対象にする探査をバランスさせることが重要とされているが，事前の取り組みを通じて，単一の演算子のみでは両者を同時に実現することが困難であることが判明した。そのため，本研究では複数の個体生成の戦略を適応的に切り替える方法を実現することで，探索と探査を自動的にバランスさせ，効率的な探索を実現する手法について検討を行った。 本研究で着目したMOEA/Dフレームワークでは，多目的問題を複数の単目的問題に分割し探索を行う。そのため，単目的問題において大域的な探索を指向する戦略と局所的な探索を指向する戦略を組み合わせることで，多目的最適化においても適応的に両方の戦略を切り替える手法を実現することができる。本研究では，この考えに基づきMOEA/D-EFモデルおよびMOEA/D-HHモデルとしてMOEA/Dを効率化した新規手法を提案した。これらのモデルはMOEA/Dフレームワークに適応的に複数の演算子を切り替えるメカニズムを導入することで探索の効率化を実現している。 論文の第二章では，MOEA/Dフレームワーク，CX戦略およびED戦略に基づく進化演算子，多目的最適化問題で使用される2つの性能メトリクスについて検討しており，第三章では，本研究で導入された進化演算子に焦点を当て，IDE，JADE，DE-IDEAL，およびCMAESについて解説している。第四章では，提案するMOEA/D-EFモデルについて説明し，第五章ではEfficiency Inspectionに基づく演算子切り替えメカニズムを組み込んだMOEA/D-HHモデルについて焦点を当て説明している。Evolutionary algorithms draw inspiration from the natural process of biological evolution, encompassing gene encoding, crossover, mutation strategies, and mechanisms of natural selection. Due to their high robustness and self-learning characteristics, evolutionary computing has emerged as an advanced global optimization technique for handling complex problems, proving more effective than traditional mathematical planning. In recent years, research has increasingly focused on utilizing evolutionary computingfor both single and multi-objective optimization problems. Our study specifically concentrates on effectively addressing multi-objective optimization problems, with a particular emphasis on individual generation methods based on the CX (Crossover) and ED (Estimation of Distribution) strategies in evolutionary algorithms. Multi-objective optimization problems, more intricate than single-objective ones, demand systematic approaches. We direct our attention to the MOEA/D (Multi-Objective Evolutionary Algorithm Based on Decomposition) framework. However, attempting to design new operators or modify classical ones to enhance overall algorithm efficiency revealed that a single operator cannot handle all search scenarios. Operator search capabilities are typically represented by exploration and exploitation methods, and concurrently possessing both capabilities is often challenging. To overcome this issue and enhance algorithmic search efficiency, it is necessary to combine multiple operators with different search characteristics into a hybrid algorithm and introduce an adaptive operator switching mechanism. Furthermore, the adaptability of operators within the framework is crucial. Many evolutionary operators were initially designed to mimic the evolution in nature and may not be well-suited for multi-objective optimization problems. In this regard, the MOEA/D framework has caught our attention. This framework can decompose multi-objective optimization problems into multiple sub-problems, allowing for the introduction of classical evolutionary operators. Simultaneously, the MOEA/D framework introduces the concept of the neighborhood of sub-problems, enabling information sharing within the neighborhood during the evolutionary process. Considering this unique feature, our primary research goal is to extend classical evolutionary operators to handle multi-objective optimization problems. To achieve this goal, we conducted detailed research and analysis on advanced evolutionary operators with different search characteristics and strategies. Subsequently, we proposed the MOEA/D-EF model and MOEA/D-HH model, introducing adaptive operator switching mechanisms to align with the MOEA/D framework. In the second chapter of the paper, we discuss the MOEA/D framework, evolutionary operators based on CX and ED strategies, and two performance metrics widely used in multi-objective optimization problems. The third chapter focuses on the introduced evolutionary operators, including IDE, JADE, DE-IDEAL, and CMA-ES. The fourth chapter introduces the MOEA/D-EF model, while the fifth chapter delves into the MOEA/D-HH model, emphasizing the operator switching mechanism based on efficiency inspection.doctoral thesi

モーションで学ぶ：ビデオ利用の影響に関する学生の視点を探る

This article explores the integration of conversation videos in English as a Foreign Language (EFL) classrooms, emphasizing students' perceptions through a paper-based survey conducted with an English Communication undergraduate class at Muroran Institute of Technology in Japan. Following the implementation of conversation videos into seven lessons, the study aimed to assess their impact on various aspects of language learning from the learners' perspective, including student interest, comprehension, pronunciation, listening skills, speaking confidence, vocabulary development, and cultural understanding. Positive student attitudes were observed across multiple areas, such as increased interest, improved cultural communication understanding and a desire for an increased use of videos. These findings highlight the potential of conversation videos in enhancing engagement and comprehension in EFL university classrooms, suggesting implications for teachers to more widely integrate this multimedia tool into their teaching practice.journal articl