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Collision-Avoidance Algorithm for Human-Symbiotic Robot
Yuji Hosoda,Kenjirou Yamamoto,Ryouko Ichinose,Saku Egawa,Junichi Tamamoto,Kouji Tsubouchi,Shinichi Yuta 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
A real-time collision-avoidance algorithm for human-symbiotic robots that are required to avoid multiple pedestrians was developed. An algorithm to predict the likelihood of a collision with obstacles was based on the relative velocities between a moving robot and multiple obstacles. An algorithm that can generate the optimum path sequence to a goal in real time was also developed. The collision-avoidance path is generated by repeating an operation to select two tangent paths that connect a via-point on a path to a collision circle of each obstacle that exists in the relative space. A robot-called EMIEW”-using these algorithms with a system for avoiding collisions with many obstacles moves at a speed of 0.8 m/s in a cluster of five people walking at 1.2 m/s. The repeat period for generating a new avoidance path is 0.5s, and the processing time for the developed algorithm in the each period is a maximum of 4 ms.
( Haruna Matsuda-hirose ),( Tomoko Yamate ),( Mizuki Goto ),( Akira Katoh ),( Hiroyuki Kouji ),( Yuya Yamamoto ),( Takashi Sakai ),( Naoto Uemura ),( Takashi Kobayashi ),( Yutaka Hatano ) 대한피부과학회 2019 Annals of Dermatology Vol.31 No.6
Background: The canonical Wnt/β-catenin signaling pathway is a fundamental regulatory system involved in various biological events. ICG-001 selectively blocks the interaction of β-catenin with its transcriptional co-activator cyclic AMP response element-binding protein (CBP). Recent studies have provided convincing evidence of the inhibitory effects of ICG-001 on Wnt-driven disease models, such as organ fibrosis, cancer, acute lymphoblastic leukemia, and asthma. However, the effects of ICG-001 in atopic dermatitis (AD) have not been investigated. Objective: To investigate whether β-catenin/CBP-dependent signaling was contributed in the pathogenesis of AD and ICG-001 could be a therapeutic agent for AD. Methods: We examined the effects of ICG-001 in an AD-like murine model generated by repeated topical application of the hapten, oxazolone (Ox). ICG-001 or vehicle alone was injected intraperitoneally every day during the development of AD-like dermatitis arising from once-daily Ox treatment. Results: Ox-induced AD-like dermatitis characterized by increases in transepidermal water loss, epidermal thickness, dermal thickness accompanied by increased myofibroblast and mast cell counts, and serum levels of thymic stromal lymphopoietin and thymus and activation- regulated chemokine, and decreases in stratum corneum hydration, were virtually normalized by the treatment with ICG-001. Elevated serum levels of periostin tended to be downregulated, without statistical significance. Conclusion: These results suggest that β-catenin/CBP-dependent signaling might be involved in the pathogenesis of AD and could be a therapeutic target. (Ann Dermatol 31(6) 631∼639, 2019)
Takayuki Takahashi,Hikaru Matsuoka,Rieko Sakurai,Jun Akatsuka,Yusuke Kobayashi,Masaru Nakamura,Takashi Iwata,Kouji Banno,Motomichi Matsuzaki,Jun Takayama,Daisuke Aoki,Yoichiro Yamamoto,Gen Tamiya 대한부인종양학회 2022 Journal of Gynecologic Oncology Vol.33 No.5
Objective: Human papillomavirus subtypes are predictive indicators of cervical intraepithelial neoplasia (CIN) progression. While colposcopy is also an essential part of cervical cancer prevention, its accuracy and reproducibility are limited because of subjective evaluation. This study aimed to develop an artificial intelligence (AI) algorithm that can accurately detect the optimal lesion associated with prognosis using colposcopic images of CIN2 patients by utilizing objective AI diagnosis. Methods: We identified colposcopic findings associated with the prognosis of patients with CIN2. We developed a convolutional neural network that can automatically detect the rate of high-grade lesions in the uterovaginal area in 12 segments. We finally evaluated the detection accuracy of our AI algorithm compared with the scores by multiple gynecologic oncologists. Results: High-grade lesion occupancy in the uterovaginal area detected by senior colposcopists was significantly correlated with the prognosis of patients with CIN2. The detection rate for high-grade lesions in 12 segments of the uterovaginal area by the AI system was 62.1% for recall, and the overall correct response rate was 89.7%. Moreover, the percentage of high-grade lesions detected by the AI system was significantly correlated with the rate detected by multiple gynecologic senior oncologists (r=0.61). Conclusion: Our novel AI algorithm can accurately determine high-grade lesions associated with prognosis on colposcopic images, and these results provide an insight into the additional utility of colposcopy for the management of patients with CIN2.