Selected Papers from the 4th International Conference on Bioinspired Systems and Cognitive Signal Processing

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Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

"Going back to our roots": second generation biocomputing

Researchers in the field of biocomputing have, for many years, successfully "harvested and exploited" the natural world for inspiration in developing systems that are robust, adaptable and capable of generating novel and even "creative" solutions to human-defined problems. However, in this position paper we argue that the time has now come for a reassessment of how we exploit biology to generate new computational systems. Previous solutions (the "first generation" of biocomputing techniques), whilst reasonably effective, are crude analogues of actual biological systems. We believe that a new, inherently inter-disciplinary approach is needed for the development of the emerging "second generation" of bio-inspired methods. This new modus operandi will require much closer interaction between the engineering and life sciences communities, as well as a bidirectional flow of concepts, applications and expertise. We support our argument by examining, in this new light, three existing areas of biocomputing (genetic programming, artificial immune systems and evolvable hardware), as well as an emerging area (natural genetic engineering) which may provide useful pointers as to the way forward.Comment: Submitted to the International Journal of Unconventional Computin

Self-Synchronization in Duty-cycled Internet of Things (IoT) Applications

In recent years, the networks of low-power devices have gained popularity. Typically these devices are wireless and interact to form large networks such as the Machine to Machine (M2M) networks, Internet of Things (IoT), Wearable Computing, and Wireless Sensor Networks. The collaboration among these devices is a key to achieving the full potential of these networks. A major problem in this field is to guarantee robust communication between elements while keeping the whole network energy efficient. In this paper, we introduce an extended and improved emergent broadcast slot (EBS) scheme, which facilitates collaboration for robust communication and is energy efficient. In the EBS, nodes communication unit remains in sleeping mode and are awake just to communicate. The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up window in partially overlapped manner within each duty-cycle to avoid message collisions. We show the theoretical convergence behavior of the scheme, which is confirmed through real test-bed experimentation.Comment: 12 Pages, 11 Figures, Journa

Applying Lexical Substitution and Text Mining for Bioinspired Engineering Design

Nature has repeated its evolution processes and developed its own “engineering” principles over a long period of time. Bioinspired design starts from the belief that nature has the most effective and optimized problem-solving schemes, which can be applied to human problems directly or indirectly. In summary, bioinspired design is the study of the design process, adapting the structure, behavior, or organic mechanisms of biology to engineering problems. In bioinspired design studies, researchers have sought a way of improving concept generation through texts. Generally, there are two problems in text-based bioinspired design. First, there is a great lexical gap between two areas—biology and engineering. Thus, understanding the context of biological text is compromised, prohibiting analogical transfer between the two domains. Second, the amount of text is too great to be assimilated by engineers. This knowledge gap makes the engineer confused by the extensive information and slows down the design process. The present work tried to apply lexical substitution and text mining theories to effectively process biological text. Regarding the matter of the lexical gap, this research developed an algorithm that translates biological terminology to words or phrases that are understandable to engineers by adapting four lexical sources: WordNet, Wikipedia, the Integrated Taxonomy Information System (ITIS), and WordNik. For the second problem, this research tried to categorize biological text based on morphological solutions by adapting the Latent Semantic Analysis (LSA) technique. Two main contributions are made in this dissertation. First of all, this work is the first attempt to directly bridge the lexical gap between biology and engineering by translating biological terminology. The existing approach to bioinspired design study involves building a thesaurus or database that connects a few engineering keywords and their biological correspondences. However, since most other biological terms remain unchanged, this research is meaningful as it attempts to overcome this limitation. The second contribution is that this research ameliorates the natural language-based bioinspired concept generation. Specifically, the accessibility to biotexts for bioinspired design seems to be improved by enabling engineers to selectively acquire biological information for their problems

University of Nebraska At Omaha Department of Biomechanics Annual Report 2019-2020

This report contains: A letter from the Director: Dr. Nick Stergiou Articles on research that impacts the community Article about the Movcentr Impact Articles on Expanding horizons Article on the people of UNO Biomechanics Student Centered articles Articles on Community Engagement and Fun.https://digitalcommons.unomaha.edu/nbcfnewsletter/1014/thumbnail.jp