Papers - YAMABA Hisaaki
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An Image Privacy Risk Detection that Maintains the Detection Performance under Interference from Reflective Components in the Image Reviewed
67 ( 3 ) 588 - 604 2026.3
Language：Japanese Publishing type：Research paper (scientific journal)
DOI： 10.20729/0002008648
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MIXVRT: MIX Visual Regression Testing Tool Which Mixes Image Comparison and HTML Code Comparison Reviewed
Aridome Naoki, Takahashi Nobuya, Katayama Tetsuro, Kita Yoshihiro, Yamaba Hisaaki, Aburada Kentaro, Okazaki Naonobu
Journal of Robotics, Networking and Artificial Life 11 ( 3 ) 214 - 219 2026.3
Language：English Publishing type：Research paper (scientific journal) Publisher：The Society of Artificial Life and Robotics
Image-based visual regression testing has the problem that it takes time required to find layout defects. Therefore, this paper develops MIXVRT (MIX Visual Regression Testing tool), which mixes image comparison and HTML code comparison. It highlights the layout defects. From evaluation experiments, we have confirmed that the time required to find layout defects can be reduced compared to the conventional methods of image-based visual regression testing, while detecting them accurately without omissions or false detections.
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Kimura Yuya, Takahashi Nobuya, Katayama Tetsuro, Kita Yoshihiro, Yamaba Hisaaki, Aburada Kentaro, Okazaki Naonobu
Journal of Robotics, Networking and Artificial Life 11 ( 3 ) 220 - 225 2026.3
Language：English Publishing type：Research paper (scientific journal) Publisher：The Society of Artificial Life and Robotics
An effective approach to manage the content entered in forms is the use of electronic forms. However, if you use a paper form, it takes time to generate electronic forms. This paper has implemented a tool for automatic entry fields detection and for labels allocation to reduce the time required to place entry fields. As a result, we have verified that the implemented tool is useful to reduce the time to place entry fields.
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Malware Classification Using Transformer-Based Modeling of API Call Sequences Reviewed
Ryoga Sakai, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Nobuya Takahashi, Mirang Park, Naonobu Okazaki
Proc. 2026 Int'l Symp. on Artificial Life and Robotics (ISAROB 2026) 1254 - 1259 2026.1
Publishing type：Research paper (international conference proceedings)
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Investigation of an Authentication Method Using Vibration-Based Secret Cues and a Virtual Dial Interface Reviewed
Takumi Kido, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Nobuya Takahashi, Mirang Park, Naonobu Okazaki
Proc. 2026 Int'l Symp. on Artificial Life and Robotics (ISAROB 2026) 1248 - 1253 2026.1
Publishing type：Research paper (international conference proceedings)
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Takatsuka Kayoko, Usuzaki Shotaro, Yamaba Hisaaki, Aburata Kentaro, Okazaki Naonobu
KAGAKU KOGAKU RONBUNSHU 52 ( 1 ) 15 - 20 2026.1
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：The Society of Chemical Engineers, Japan
The spread of infectious diseases in the livestock industry results in severe economic losses and social disruption. This study focuses on the 2010 outbreak of foot-and-mouth disease (FMD) in Miyazaki Prefecture, Japan, and proposes a framework for quantitatively assessing farm-level susceptibility to infection through the construction of a Potential Infection Risk Index (λ). This index integrates multiple factors, including spatial proximity between farms, herd size, and livestock species. Statistical analysis reveals that λ values significantly differ between infected and uninfected farms, with the disparity widening as distance from the infection source decreases. These findings indicate that the spread of infection is strongly influenced by both geographic proximity and structural characteristics of farms. Furthermore, λ enables objective and quantitative identification of high-risk farms, supporting practical responses such as the prioritized allocation of limited disease control resources and the flexible application of hygiene management standards. A case study simulating farm relocation demonstrates that λ-based site selection effectively reduces infection risk, thereby validating the index as a practical and economically rational decision-support indicator. This approach also suggests the potential application of λ in long-term farm siting and structural planning. Additionally, the study envisions a comprehensive disease control support system centered on λ and its adjusted form (λ′), incorporating features such as risk visualization, hygiene-related corrections, tailored alerts and recommendations, and integration with administrative decision-making processes. Future work will focus on the development and implementation of such decision-support tools, with the ultimate goal of enhancing disease control efforts and contributing to the sustainable development of the livestock industry.
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Takahashi Nobuya, Kamada Taiki, Usuzaki Shotaro, Aburada Kentaro, Yamaba Hisaaki, Park Mirang, Okazaki Naonobu
IEICE Communications Express 14 ( 12 ) 441 - 444 2025.12
Language：English Publishing type：Research paper (scientific journal) Publisher：一般社団法人 電子情報通信学会
In this study, we propose a text-based CAPTCHA that utilizes human visual completion to prevent automated programs from getting through, without affecting human cognition. This CAPTCHA requires users to enter the reading of the kanji strings, whose centers are hidden behind a black bar. This method makes it challenging for machines to recognize the characters, while still allowing humans to identify the original text through their visual completion ability. We evaluate both the usability and security of the proposed CAPTCHA. To assess usability, we observed how humans respond to the CAPTCHA challenge. For the security evaluation, we tested the machine’s ability to read the kanji using a Convolutional Neural Network (CNN). The results showed that the proposed CAPTCHA achieves a success rate comparable to traditional CAPTCHAs, with a slightly shorter response time than a similar type of CAPTCHA. Furthermore, security experiments have shown that it exhibits a certain degree of resistance against simple convolutional neural networks.
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An Attempt to Improve the Flow Count Estimation Accuracy During the Collection Phase for Sketch-Reconstruction-Based In-Band Network Telemetry Reviewed
Shotaro Usuzaki, Kosei Iwasa, Nobuya Takahashi, Kentaro Aburada, Hisaaki Yamaba, Mirang Park, Naonobu Okazaki
Proc. of The 9th International Conference on Information Technology 2025.11
Language：English Publishing type：Research paper (international conference proceedings)
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Applying Deep Reinforcement Learning to Semiconductor Manufacturing Scheduling Problems Reviewed
Kaito Hashimoto, Susumu Katayama, Satoru Arimura, Kousuke Hara, Hisaaki Yamaba
Proc. of 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems 1071 - 1080 2025.9
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
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Slow HTTP POST DDoS Attack Prevention Method that Monitors Payload Size and Number of Connections Reviewed
Yuya Ozaki, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Mirang Park, Naonobu Okazaki
Proc. of the 28-th International Conference on Network-Based Information Systems (NBiS-2025) 22 - 31 2025.9
Publishing type：Research paper (international conference proceedings)
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An Attempt of Personal Identification Using S-EMG Signals from Hand Gestures Measured at Multiple Points Reviewed
Hisaaki Yamaba, Naruki Komori ,Shotaro Usuzaki, Kentaro Aburada, Tetsuro Katayama, Naonobu Okazaki
Proc. 2025 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN 2025.7
Authorship：Lead author, Corresponding author Publishing type：Research paper (international conference proceedings)
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Aridome N., Katayama T., Kita Y., Yamaba H., Aburada K., Okazaki N.
Proceedings of International Conference on Artificial Life and Robotics 575 - 579 2025.2
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings of International Conference on Artificial Life and Robotics
As a method for detecting layout defects in web pages, image-based visual regression testing is proposed. However, it has the problem that it takes time to detect unintended layout differences that are not based on HTML code changes. This paper proposes a prototype of MixVRT which is a tool to detect layout defects in web pages. It is a visual regression testing tool that highlights layout defects in web pages. From evaluation experiments, the time find to layout defects can be reduced.
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Kimura Y., Katayama T., Kita Y., Yamaba H., Aburada K., Okazaki N.
Proceedings of International Conference on Artificial Life and Robotics 580 - 584 2025.2
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings of International Conference on Artificial Life and Robotics
The digitalization of forms is being promoted. One of the effective ways to manage contents filled in fields is using electronic forms. Several tools have been developed to generate them automatically. However, when you use a paper form, the layout of the original form may change, and it takes time to generate electronic one because it is necessary to place fill-in fields on an electronic form by dragging with a mouse. This paper proposes a method for automatic fill-in fields detection and labels assignment to reduce time required to place fill-in fields without changing the layout. The proposed method can reduce the time to place fill-in fields.
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Introducing Generative AI into Unrealistic Image CAPTCHA for Effective Image Generation Reviewed
Kana Saiki, Hisaaki Yamaba, Shotaro Usuzaki, Kentaro Aburada, Masayuki Mukunoki, Mirang Park, Naonobu Okazaki
Proc. 2025 Int'l Symp. on Artificial Life and Robotics (ISAROB 2025) 1085 - 1090 2025.1
Authorship：Corresponding author Publishing type：Research paper (international conference proceedings)
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Introduction of Feature Points in Images for Improvement of Finding Letters Type CAPTCHA Based on Neural Style Transfer Reviewed
Ramu Kiura, Hisaaki Yamaba, Shotaro Usuzaki, Kentaro Aburada, Masayuki Mukunoki, Mirang Park, Naonobu Okazaki
Proc. 2025 Int'l Symp. on Artificial Life and Robotics (ISAROB 2025) 1079 - 1084 2025.1
Authorship：Corresponding author Publishing type：Research paper (international conference proceedings)
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Investigation of Detection Methods for Trojaned DNNs under Specific Conditions Reviewed
Shunya Izaki, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Tetsuro Katayama, Mirang Park, Naonobu Okazaki
Proc. 2025 Int'l Symp. on Artificial Life and Robotics (ISAROB 2025) 1074 - 1078 2025.1
Publishing type：Research paper (international conference proceedings)
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A study of Collaborative malware detection using item response theory Reviewed
Takuro Inada, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Tetsuro Katayama, Mirang Park, Naonobu Okazaki
Proc. 2025 Int'l Symp. on Artificial Life and Robotics (ISAROB 2025) 1070 - 1073 2025.1
Publishing type：Research paper (international conference proceedings)
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Extending BWDM to Support Various Types and Recursive Definitions in VDM++ Test Case Generation Reviewed
Takakura Shota, Katayama Tetsuro, Yamaba Hisaaki, Aburada Kentaro, Okazaki Naonobu, Kita Yoshihiro
Journal of Advances in Artificial Life Robotics 4 ( 3 ) 167 - 171 2025
Language：English Publishing type：Research paper (scientific journal) Publisher：株式会社 ALife Robotics
Generating test cases from VDM++ formal specifications, which help to eliminate ambiguities, is
both time-consuming and labor-intensive. To solve this problem, our laboratory has developed
BWDM, a tool for automatic test case generation from VDM++ specifications. However, the
original BWDM only supports integer types and cannot handle test cases for operations and
functions with recursive structures. To enhance BWDM's usefulness, this paper introduces
extensions to address these limitations. The results confirm that the extended BWDM can reduce
test case generation time compared to manual methods. -
Applying Deep Reinforcement Learning to Semiconductor Manufacturing Scheduling Problems Reviewed
Hashimoto K., Katayama S., Arimura S., Hara K., Yamaba H.
Procedia Computer Science 270 1071 - 1080 2025
Publishing type：Research paper (scientific journal) Publisher：Procedia Computer Science
In this paper, we proposed a scheduling method for semiconductor manufacturing systems by extending that for a job shop scheduling problem (JSSP) using deep reinforcement learning approach. The proposed method can handle the unique characteristics of the semiconductor manufacturing process, i.e., the reentrancy and the flexibility. The advantage of the proposed method is scalable and can effectively handle increasing problem sizes. From the results of experiments, we confirmed that even when small-sized tasks were used in the training, the scheduling performance for large-sized tasks was equal to or better than the case using large-sized tasks in the training.
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Yamaba H., Komori N., Usuzaki S., Aburada K., Katayama T., Okazaki N.
Icce Taiwan 2025 12th IEEE International Conference on Consumer Electronics Taiwan Generative AI in Innovative Consumer Technology Proceedings 111 - 112 2025
Publishing type：Research paper (scientific journal) Publisher：Icce Taiwan 2025 12th IEEE International Conference on Consumer Electronics Taiwan Generative AI in Innovative Consumer Technology Proceedings
Mobile devices such as smartphones and tablets are now deeply integrated into daily life. To prevent shoulder surfing attacks, we propose a user authentication method for mobile devices based on surface electromyogram (s-EMG) signals. The method uses a “pass-gesture,” a sequence of hand gestures that can be changed like a password. Fingerspelling was adopted as the source of gesture candidates. Previous studies confirmed high accuracy in identifying gestures performed by the same subject. This paper focuses on evaluating subject specificity-specifically, confirming that a model trained on one user fails to recognize gestures performed by another. Experimental results show that the system does not generalize across users, indicating robustness against impersonation.