Nano Sistemlerde Hücreler Arası Haberleşmenin Analiz Edilmesi

Yıl 2021, Cilt: 4 Sayı: 2, 203 - 211, 23.09.2021

İbrahim Işık , M. Emin Tağluk , Esme Işık

https://doi.org/10.38016/jista.920659

Öz

Farklı canlı türleri farklı zeka seviyelerine sahip olduğundan, akıl ve zekanın beyinle bir bağlantısının olabileceği düşünülmektedir. Akıl, bilinç ve zaka insanlık tarihinden beri bilim insanlarını etkileyen en etkileyici kavramlar arasında olmuştur. Ancak bilinci, yalnızca sinir sisteminin veya beynin bir ürünü olarak görmenin de uygun olmayacağı düşünülmektedir. Beynin, yaratıcılık, düşünce ve duygu vs. gibi organizasyonlardan sorumlu olduğu bilinmektedir. Bilincin varlığı için ise sinir sistemi veya beynin gerekli olmadığı birçok çalışma tarafından daha önce ispatlanmıştır. Bunun en basit örneği bitkilerin herhangi bir sinir sistemi veya beyni olmamasına rağmen güneşe yönelebilme bilinçlerinin olmasıdır. Bilinçli bir nano haberleşme modelin tasarlanabilmesi için öncelikle biyolojik canlıların ürettiği sinyallerin tasarlanan bu model ile elde edilmesi gerektiği düşünülmektedir. Çünkü canlıların bütün hücrelerinin bu sinyaller (aksiyon potansiyel) aracılığı ile birbiri arasında iletişim kurduklarına inanılmaktadır. Bu sebeple bu çalışma kapsamında, biyolojik hücrelerin ürettiği aksiyon potansiyel sinyaline neredeyse birebir benzer sinyal üreten elektronik bir devre tasarlanmıştır. Üretilen aksiyon potansiyelin gerçek bir nöron hücresinin ürettiği aksiyon potansiyele yakın olabilmesi için literatürdeki elektronik modellerde kullanılan elemanlar incelendikten sonra böyle bir sistem geliştirilmiş ve bu sistemde kullanılan parametrelerin değeri de yine üretilen aksiyon potansiyelin benzerliğini arttıracak şekilde uzun süren denemeler sonunda hassas bir şekilde tespit edilmiştir. Daha sonra ise tasarlanan model ile iki hücrenin birbiri ile haberleşmesinden elde edilen veriler incelenmiştir.

Anahtar Kelimeler

Yapay zeka, Yapay bilinç, Nano sistemler, Unipolar junction transistör

Analyzing of Intercell Communication in Nano Systems

Öz

Since different living species have different intelligence levels, it is thought that intelligence and mind may have a connection with the brain. Mind, consciousness and intelligence have been among the most influential concepts that have influenced scientists since human history. However, it is thought that it would not be appropriate to view consciousness only as a product of the nervous system or the brain. Your brain, creativity, thoughts and emotions etc. It is known to be responsible for such organizations. It is previously defined in several studies that the brain or nervous system is not necessary for the presence of consciousness. The simplest example of this is that plants do not have any nervous system or brain, but have the consciousness to turn towards the sun. In order to design a conscious nano communication model, it is thought that the signals produced by biological cells must be obtained with this designed model. Because it is believed that all the cells of living things communicate with each other through these signals (action potentials). For this reason, within the scope of this study, an electronic circuit that produces an almost same signal to the action potential signal produced by biological cells has been designed. In order for the produced action potential to be close to the action potential produced by a real neuron cell, such a system was developed after examining the components used in the electronic models in the literature, and the value of the parameters used in this system was determined precisely after long trials, again increasing the similarity of the produced action potential. Then, the data are obtained from the communication of two cells with each other with the designed model were analyzed.

Anahtar Kelimeler

Artificial intelligence, Artificial consciousness, Nano systems, Unipolar junction transistor

Kaynakça

• Grazian, S., Webb. T. 2014. “A Mechanistic Theory of Consciousness.” International Journal of Machine Consciousness 6(2).
• Lamme, V. A. 2003. “Why Visual Attention and Awareness Are Different.” Trends in Cognitive Sciences 7(1).
• Akan, O. B. n.d. “Icimizdeki Internet Molekuler Haberlesme ve Nanoaglar.” Retrieved February 10, 2018 (http://panorama.khas.edu.tr/icimizdeki-internet-molekuler-haberlesme-ve-nanoaglar-154).
• Amanda Sharke, Noel Sharkey. 2010. “Granny and the Robots: Ethical Issues in Robot Care for the Elderly.” Ethics and Information Technology 14.
• Banfield, Jeffrey D., and Adrian E. Raftery. 1992. “Ice Floe Identification in Satellite Images Using Mathematical Morphology and Clustering about Principal Curves.” Journal of the American Statistical Association 87(417):7–16.
• Barreto, Guilherme A., Aluizio F. R. Araújo, Christof Dücker, and Helge Ritter. 2002. “A Distributed Robotic Control System Based on a Temporal Self-Organizing Neural Network.” IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 32(4):347–57. doi: 10.1109/TSMCC.2002.806067.
• Bilal Er, Mehmet, and Ibrahim Berkan Aydilek. 2019. “Music Emotion Recognition by Using Chroma Spectrogram and Deep Visual Features.” International Journal of Computational Intelligence Systems 12(2):1622–34. doi: 10.2991/ijcis.d.191216.001.
• Buttazzo, Giorgio. 2008. “Artificial Consciousness: Hazardous Questions (and Answers).” Artificial Intelligence in Medicine 44(2):139–46. doi: 10.1016/j.artmed.2008.07.004.
• Chandra, Rohitash. 2017. “Towards an Affective Computational Model for Machine Consciousness.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10638 LNCS:897–907. doi: 10.1007/978-3-319-70139-4_91.
• Dehaene, Stanislas, Hakwan Lau, and Sid Kouider. 2017. “What Is Consciousness, and Could Machines Have It?” Science 358(6362):486–92. doi: 10.1126/science.aan8871.
• Dezfouli, A., and Balleine, B. 2013. “Actions, Action Sequences and Habits: Evidence That Goal-Directed and Habitual Action Control Are Hierarchically Organized.” PLoS Comput. Biol.
• Eter, P., and Andr As. 2002. “KERNEL-KOHONEN NETWORKS.” 12(2):117–35.
• Gamez, D. 2008. “Progress in Machine Consciousness.” Consciousness and Cognition 17(3).
• Harvey Lodish, Arnold Berk, S Lawrence Zipursky, Paul Matsudaira, David Baltimore, and James Darnell. 2000. Molecular Cell Biology. Vol. 29.
• J. A. Reggia. 2013. “The Rise of Machine Consciousness: Studying Consciousness with Computational Models.” Neural Networks 44.
• J. A. Starzyk, D. K. Prasad. 2011. “A Computational Model of Machine Consciousnes.” International Journal of Machine Consciousness 3(2).
• Kak, Subhash. n.d. “Https://Subhashkak.Medium.Com/Artificial-Intelligence-and-Consciousness-6b5ff2e5b5a.”
• Kinouchi, Yasuo, and Kenneth James Mackin. 2018. “A Basic Architecture of an Autonomous Adaptive System with Conscious-like Function for a Humanoid Robot.” Frontiers Robotics AI 5(APR). doi: 10.3389/frobt.2018.00030.
• Kinouchi, Yasuo, Kenneth James MacKin, and Pitoyo Hartono. 2018. “A Conscious AI System Based on Recurrent Neural Networks Applying Dynamic Information Equilibrium.” CEUR Workshop Proceedings 2287(December). doi: 10.29007/2hjj.
• Lake, Brenden M., Tomer D. Ullman, Joshua B. Tenenbaum, and Samuel J. Gershman. 2017. “Building Machines That Learn and Think like People.” Behavioral and Brain Sciences 40(2012):1–58. doi: 10.1017/S0140525X16001837.
• M. S. Graziano. 2013. Consciousness and the Social Brain. Oxford University Press.
• M. S. Graziano, S. Kastner. 2011. “Human Consciousness and Its Relationship to Social Neuroscience: A Novel Hypothesis.” Cognitive Neuroscience 2(2).
• Marchetti, Giorgio. 2018. “Consciousness: A Unique Way of Processing Information.” Cognitive Processing 4(19).
• Moravec, Hans P. n.d. Mind Children: The Future of Robot and Human Intelligence. Harvard Un.
• Neukart, Florian, Sorin Aurel Moraru, Costin Marius Grigorescu, and Peter Szakacs-Simon. 2012. “Cortical Artificial Neural Networks and Their Evolution - Consciousness-Inspired Data Mining.” Proceedings of the International Conference on Optimisation of Electrical and Electronic Equipment, OPTIM 1126–33. doi: 10.1109/OPTIM.2012.6231782.
• P. Dario, E. Guglielmelli, C. Laschi. 2001. “Humanoids and Personal Robots: Design and Experiments.” Journal of Robotic Systems 18(12).
• Pandey, Subhash Chandra. 2018. “Can Artificially Intelligent Agents Really Be Conscious?” Sadhana - Academy Proceedings in Engineering Sciences 43(7):1–17. doi: 10.1007/s12046-018-0887-x.
• Sanz R. 2005. “Design and Implementation of an Artificial Conscious Machine.” in IWAC2005, Proceedings of. Savtchenko, Leonid P., Mu Ming Poo, and Dmitri A. Rusakov. 2017. “Electrodiffusion Phenomena in Neuroscience : A Neglected Companion.” Nature Publishing Group 18(10):598–612. doi: 10.1038/nrn.2017.101.
• Scellie,B., Bengio, Y. 2017. “Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation.” Front. Comput. Neurosci 11(24). Simon Peter van Rysewyk, Matthijs Pontier. 2015. Machine Medical Ethics. Springer, Cham.
• Singh, Sushant, and Naresh C. Bal. 2017. “Membrane Biophysics.” Introduction to Biomolecular Structure and Biophysics: Basics of Biophysics 183–204. doi: 10.1007/978-981-10-4968-2_7.
• Xu, Xiaoran, Wei Feng, Zhiqing Sun, and Zhi-Hong Deng. 2019. “Neural Consciousness Flow.” 1–30.
• Yamazaki, Kimitoshi, Yoshiaki Watanabe, Kotaro Nagahama, Kei Okada, and Masayuki Inaba. 2010. “Recognition and Manipulation Integration for a Daily Assistive Robot Working on Kitchen Environments.” 2010 IEEE International Conference on Robotics and Biomimetics, ROBIO 2010 (October 2016):196–201. doi: 10.1109/ROBIO.2010.5723326.
• Yin, Hujun. 2008. “The Self-Organizing Maps: Background, Theories, Extensions and Applications.” Studies in Computational Intelligence 115:715–62. doi: 10.1007/978-3-540-78293-3_17.
• Zhao, Tong, Yiqian Zhu, Hailiang Tang, Rong Xie, Jianhong Zhu, and John H. Zhang. 2019. “Consciousness: New Concepts and Neural Networks.” Frontiers in Cellular Neuroscience 13(July):1–7. doi: 10.3389/fncel.2019.00302.