Suffering from dirty strong supersonic attacks
1supersonic attacked
AAS
30YAMAGUTIseisei [sage]
31YAMAGUTIseisei [sage]
32YAMAGUTIseisei [sage]
33YAMAGUTIseisei [sage]
34YAMAGUTIseisei [sage]
35YAMAGUTIseisei [sage]
36YAMAGUTIseisei [sage]
37YAMAGUTIseisei [sage]
38オーバーテクナナシー [m9(^Д^)]
39オーバーテクナナシー
AAS
I'm suffering from dirty strong supersonic attacks!! Supersonic terrorisms!!
The supersonic attacker is also in Yamaguchi city.
The supersonic attacker is also in Yamaguchi city.
2017/11/29(水)01:34:15.97(Yul9QZKXc)
30YAMAGUTIseisei [sage]
This is the first study on SSVEP magnitude prediction toward a novel SSVEP-BCI.
We created datasets from experiments on varying SSVEP magnitude responses.
The Random Forest Regression was then proposed as the algorithm for instantaneous SSVEP magnitude prediction.
The experimental results were obtained from ten subjects using leave-one-subject-out cross validation seem promising.
The instantaneous changes in predicted SSVEP magnitude can be mapped into the speed controller for brain-controlled applications (e.g. robot control).
Here, an online-like system was conducted using a simulated mobile robot.
The experiments involved streaming back the real SSVEP responses of varying magnitudes to control the moving speed of the robot.
For practical purposes, a single (Oz) EEG channel was used through all the experiments.
The advantage of the SSVEP magnitude prediction is that it has an ability to maintain stability when controlling the robotic.
In the near future, the outcomes from this work will be implemented in other smooth brain-controlled applications such as accelerating or decelerating the speed of a mobile robot or a robotic arm.
Page 10>10
We created datasets from experiments on varying SSVEP magnitude responses.
The Random Forest Regression was then proposed as the algorithm for instantaneous SSVEP magnitude prediction.
The experimental results were obtained from ten subjects using leave-one-subject-out cross validation seem promising.
The instantaneous changes in predicted SSVEP magnitude can be mapped into the speed controller for brain-controlled applications (e.g. robot control).
Here, an online-like system was conducted using a simulated mobile robot.
The experiments involved streaming back the real SSVEP responses of varying magnitudes to control the moving speed of the robot.
For practical purposes, a single (Oz) EEG channel was used through all the experiments.
The advantage of the SSVEP magnitude prediction is that it has an ability to maintain stability when controlling the robotic.
In the near future, the outcomes from this work will be implemented in other smooth brain-controlled applications such as accelerating or decelerating the speed of a mobile robot or a robotic arm.
Page 10
2019/04/24(水)10:34:03.46(5ZbN1Z79QBE:154205879-2BP(3))
31YAMAGUTIseisei [sage]
REFERENCES
2019/04/24(水)10:34:32.47(5ZbN1Z79QBE:58745164-2BP(3))
32YAMAGUTIseisei [sage]
[8]
E. Yin, Z. Zhou, J. Jiang, F. Chen, Y. Liu, and D. Hu,
`` A novel hybrid bci speller based on the incorporation of ssvep into the p300 paradigm, ''
Journal of neural engineering, vol. 10, no. 2, p. 026012, 2013.
[9]
E. Yin, Z. Zhou, J. JIang, F. Chen, Y. Liu, and D. Hu,
`` A speedy hybrid bci spelling approach combining p300 and ssvep, ''
IEEE Transactions on Biomedical Engineering, vol. 61, no. 2, pp. 473483, 2014.
[10]
Y. Wang, X. Chen, X. Gao, and S. Gao,
`` A benchmark dataset for SSVEP-based brain-computer interfaces, ''
IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 25, no. 10, pp. 17461752, Oct 2017.
[11]
B. Allison, B. Graimann, and G. Pfurtscheller,
Brain-computer Interfaces: Revolutionizing Human-computer Interaction.
Springer, 2010.
[12]
X. Chen, Y. Wang, S. Zhang, S. Gao, Y. Hu, and X. Gao,
`` A novel stimulation method for multi-class ssvep-bci using intermodulation frequencies, ''
Journal of neural engineering, vol. 14, no. 2, p. 026013, 2017.
[13]
Y. J. Kim, M. Grabowecky, K. A. Paller, K. Muthu, and S. Suzuki,
`` Attention induces synchronization-based response gain in steady-state visual evoked potentials, ''
Nature neuroscience, vol. 10, no. 1, p. 117, 2007.
[14]
`` Open source brain-computer interfaces, ''
http://openbci.com/
.
E. Yin, Z. Zhou, J. Jiang, F. Chen, Y. Liu, and D. Hu,
`` A novel hybrid bci speller based on the incorporation of ssvep into the p300 paradigm, ''
Journal of neural engineering, vol. 10, no. 2, p. 026012, 2013.
[9]
E. Yin, Z. Zhou, J. JIang, F. Chen, Y. Liu, and D. Hu,
`` A speedy hybrid bci spelling approach combining p300 and ssvep, ''
IEEE Transactions on Biomedical Engineering, vol. 61, no. 2, pp. 473483, 2014.
[10]
Y. Wang, X. Chen, X. Gao, and S. Gao,
`` A benchmark dataset for SSVEP-based brain-computer interfaces, ''
IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 25, no. 10, pp. 17461752, Oct 2017.
[11]
B. Allison, B. Graimann, and G. Pfurtscheller,
Brain-computer Interfaces: Revolutionizing Human-computer Interaction.
Springer, 2010.
[12]
X. Chen, Y. Wang, S. Zhang, S. Gao, Y. Hu, and X. Gao,
`` A novel stimulation method for multi-class ssvep-bci using intermodulation frequencies, ''
Journal of neural engineering, vol. 14, no. 2, p. 026013, 2017.
[13]
Y. J. Kim, M. Grabowecky, K. A. Paller, K. Muthu, and S. Suzuki,
`` Attention induces synchronization-based response gain in steady-state visual evoked potentials, ''
Nature neuroscience, vol. 10, no. 1, p. 117, 2007.
[14]
`` Open source brain-computer interfaces, ''
http://openbci.com/
.
2019/04/24(水)10:34:59.51(5ZbN1Z79QBE:176235089-2BP(3))
33YAMAGUTIseisei [sage]
[15]
K. Cho, B. Van Merri boer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio,
`` Learning phrase representations using rnn encoder-decoder for statistical machine translation, ''
arXiv preprint arXiv:1406.1078, 2014.
[16]
F. Chollet et al., `` Keras, ''
http://github.com/fchollet/keras/
, 2015.
[17]
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay,
`` Scikit-learn: Machine learning in Python, ''
Journal of Machine Learning Research, vol. 12, pp. 28252830, 2011.
[18]
M. F. E. Rohmer, S. P. N. Singh,
`` V-rep: a versatile and scalable robot simulation framework, ''
in Proc. of The International Conference on Intelligent Robots and Systems (IROS), 2013.
[19]
S. Dasgupta, D. Goldschmidt, F. Wrgtter, and P. Manoonpong,
`` Distributed recurrent neural forward models with synaptic adaptation and cpg-based control for complex behaviors of walking robots, ''
Frontiers in Neurorobotics, vol. 9, p. 10, 2015.
[Online]. Available: http://www.frontiersin.org/article/10.3389/fnbot.2015.00010
K. Cho, B. Van Merri boer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio,
`` Learning phrase representations using rnn encoder-decoder for statistical machine translation, ''
arXiv preprint arXiv:1406.1078, 2014.
[16]
F. Chollet et al., `` Keras, ''
http://github.com/fchollet/keras/
, 2015.
[17]
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay,
`` Scikit-learn: Machine learning in Python, ''
Journal of Machine Learning Research, vol. 12, pp. 28252830, 2011.
[18]
M. F. E. Rohmer, S. P. N. Singh,
`` V-rep: a versatile and scalable robot simulation framework, ''
in Proc. of The International Conference on Intelligent Robots and Systems (IROS), 2013.
[19]
S. Dasgupta, D. Goldschmidt, F. Wrgtter, and P. Manoonpong,
`` Distributed recurrent neural forward models with synaptic adaptation and cpg-based control for complex behaviors of walking robots, ''
Frontiers in Neurorobotics, vol. 9, p. 10, 2015.
[Online]. Available: http://www.frontiersin.org/article/10.3389/fnbot.2015.00010
2019/04/24(水)10:36:24.64(5ZbN1Z79QBE:51401873-2BP(3))
34YAMAGUTIseisei [sage]
>>8
To develop a novel SSVEP-BCI paradigm for a brain-machine control system which allows users to continuously increase/decrease the moving speed of the application , this study hypothesizes that magnitude variation would help attain the goal.
To develop a novel SSVEP-BCI paradigm for a system which allows users to continuously increase/decrease the moving speed of the application (i.e. speed robot movements), this study hypothesizes that magnitude variation would help attain the goal.
application (i.e. speed robot movements)
http://miraitranslate.com/trial/
ユーザがアプリケーション(速度ロボットの動作)の移動速度を連続的に増加/減少させることを可能にする脳機械制御システムのための新しいSSVEP‐BCIパラダイムを開発するために,本研究では規模変動が目標の達成を助けるであろうと仮定した。
To develop a novel SSVEP-BCI paradigm for a brain-machine control system which allows users to continuously increase/decrease the moving speed of the application , this study hypothesizes that magnitude variation would help attain the goal.
To develop a novel SSVEP-BCI paradigm for a system which allows users to continuously increase/decrease the moving speed of the application (i.e. speed robot movements), this study hypothesizes that magnitude variation would help attain the goal.
application (i.e. speed robot movements)
http://miraitranslate.com/trial/
ユーザがアプリケーション(速度ロボットの動作)の移動速度を連続的に増加/減少させることを可能にする脳機械制御システムのための新しいSSVEP‐BCIパラダイムを開発するために,本研究では規模変動が目標の達成を助けるであろうと仮定した。
2019/04/27(土)07:57:25.89(Ay/E8QVQTBE:39163182-2BP(3))
35YAMAGUTIseisei [sage]
2019/07/12(金)20:46:27.81(f5bVsPQ5K)
36YAMAGUTIseisei [sage]
II.
CURRENT STATUS
Cystic ducts (9 types), aortic arches (4 types) and renal veins (4 types) with variation were modeled in OBJ format.
Fig.2 shows examples from those cystic duct models.
The cystic duct models were merged to a surgery simulation scene using multi-resolution modeling approach and a synchronization approach for maintaining consistency of binary trees [3].
In this project, many studies have to be done, eg clinical verification of those models, optimization for faster performance of the surgical simulator with more complex organ structure and so on.
As a future work, this theme will be reported.
ACKNOWLEDGMENT
Research supported by SCOPE fund and JSPS KAKENHI Grant Number25282154.
a) Shiga University of Medical Science, Otsu, Shiga 6062192 Japan (corresponding 1st author to provide phone: +81-77-548-2641; fax: +81-77-548-2412; e-mail: kom@belle.shiga-med.ac.jp).
b) Ritsumeikan University, Kusatsu, Shiga 5258577 Japan.
Figure 1.
Overview of our surgery simulation system
Figure 2.
Some modular model of cystic ducts
CURRENT STATUS
Cystic ducts (9 types), aortic arches (4 types) and renal veins (4 types) with variation were modeled in OBJ format.
Fig.2 shows examples from those cystic duct models.
The cystic duct models were merged to a surgery simulation scene using multi-resolution modeling approach and a synchronization approach for maintaining consistency of binary trees [3].
In this project, many studies have to be done, eg clinical verification of those models, optimization for faster performance of the surgical simulator with more complex organ structure and so on.
As a future work, this theme will be reported.
ACKNOWLEDGMENT
Research supported by SCOPE fund and JSPS KAKENHI Grant Number25282154.
a) Shiga University of Medical Science, Otsu, Shiga 6062192 Japan (corresponding 1st author to provide phone: +81-77-548-2641; fax: +81-77-548-2412; e-mail: kom@belle.shiga-med.ac.jp).
b) Ritsumeikan University, Kusatsu, Shiga 5258577 Japan.
Figure 1.
Overview of our surgery simulation system
Figure 2.
Some modular model of cystic ducts
2019/07/12(金)20:47:05.39(f5bVsPQ5K)
37YAMAGUTIseisei [sage]
REFERENCES
[1]
V. Sherman, LS Feldman, D. Stanbridge, R. Kazmi, GM Fried,
“Assessing the learning curve for the acquisition of laparoscopic skills on a virtual reality simulator”
, Surg Endosc, 19: 678?682, 2005
[2]
FH Netter,
“Atlas of Human Anatomy (Book style with paper title and editor),”
in Plastics , 2nd ed. vol. 3, J. Peters, Ed. New York: McGraw-Hill, 1964, pp. 15–64.
[3]
K. Tagawa, H. Tanaka, K. Yoshimasa, M. Komori, and S. Morikawa,
“Expression of cystohepatic duct anomaly using modular structured organ model in a laparoscopic surgery simulator”
, Int J CARS, 7 (Suppl 1), S194-S196, 2012.
R-252
[1]
V. Sherman, LS Feldman, D. Stanbridge, R. Kazmi, GM Fried,
“Assessing the learning curve for the acquisition of laparoscopic skills on a virtual reality simulator”
, Surg Endosc, 19: 678?682, 2005
[2]
FH Netter,
“Atlas of Human Anatomy (Book style with paper title and editor),”
in Plastics , 2nd ed. vol. 3, J. Peters, Ed. New York: McGraw-Hill, 1964, pp. 15–64.
[3]
K. Tagawa, H. Tanaka, K. Yoshimasa, M. Komori, and S. Morikawa,
“Expression of cystohepatic duct anomaly using modular structured organ model in a laparoscopic surgery simulator”
, Int J CARS, 7 (Suppl 1), S194-S196, 2012.
R-252
2019/07/12(金)20:48:44.31(f5bVsPQ5K)
38オーバーテクナナシー [m9(^Д^)]
統合失調症
2020/08/14(金)16:29:20.09
39オーバーテクナナシー
人を殺すと地獄に堕ちるとかお子ちゃまみたいなこと言ってるオトナには唖然とするよな
騒音に温室効果カ゛スにコロナにとまき散らさせて、気侯変動させて海水温上昇させてかつてない量の水蒸氣を発生させて、
土砂崩れに洪水、暴風．猛暑、大雪にと災害連発させて地球破壊して、静音が生命線の知的産業に威力業務妨害して根絶やしにして、
医療崩壊させて助かる命まで奪い取って多くの無辜の住民の生命と財産を破壊して私腹を肥やしてる斎藤鉄夫ら世界最悪の殺人テロ組織
国土破壊省だのJΑLた゛の機長殴って駆け付けた警官まで殴打して現行犯逮捕の酒気帯び運転ANAだのクソアヰヌドゥだの酒飲んで業務
してるクサイマ―クた゛のゴキブリフライヤーだのテロリストを皆殺しにしたら、人のみならず多くの生命が救われるんだから、どんな理屈を
こねたところで．明らかに天国行きだろ、税金で票買って腐敗を謳歌してきた腐敗の権化を討ち取った民主主義の教祖山上大先生も完全に
天国行き確定だし，少しは物事を論理的に理解できる人としての最低限の能カくらい身に着けよう!
(羽田)https://www.call4.jp/info.Php?tyΡe=itｅms&id＝I００00062 , ttРs://haneda-project.jimdofree.Com/
(成田］ttps：//n-souonhigaisosyoudan.amеbaownd.сom/
(テロ組織)ttps:/／i.imgur.com/hnli1ga.jpeg
騒音に温室効果カ゛スにコロナにとまき散らさせて、気侯変動させて海水温上昇させてかつてない量の水蒸氣を発生させて、
土砂崩れに洪水、暴風．猛暑、大雪にと災害連発させて地球破壊して、静音が生命線の知的産業に威力業務妨害して根絶やしにして、
医療崩壊させて助かる命まで奪い取って多くの無辜の住民の生命と財産を破壊して私腹を肥やしてる斎藤鉄夫ら世界最悪の殺人テロ組織
国土破壊省だのJΑLた゛の機長殴って駆け付けた警官まで殴打して現行犯逮捕の酒気帯び運転ANAだのクソアヰヌドゥだの酒飲んで業務
してるクサイマ―クた゛のゴキブリフライヤーだのテロリストを皆殺しにしたら、人のみならず多くの生命が救われるんだから、どんな理屈を
こねたところで．明らかに天国行きだろ、税金で票買って腐敗を謳歌してきた腐敗の権化を討ち取った民主主義の教祖山上大先生も完全に
天国行き確定だし，少しは物事を論理的に理解できる人としての最低限の能カくらい身に着けよう!
(羽田)https://www.call4.jp/info.Php?tyΡe=itｅms&id＝I００00062 , ttРs://haneda-project.jimdofree.Com/
(成田］ttps：//n-souonhigaisosyoudan.amеbaownd.сom/
(テロ組織)ttps:/／i.imgur.com/hnli1ga.jpeg
2023/10/22(日)20:49:25.46(HKomAKF4A)