43 research outputs found
Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications
Investigation of visual pathways in honeybees (Apis mellifera) and desert locusts (Schistocerca gregaria): anatomical, ultrastructural, and physiological approaches
Many insect species demonstrate sophisticated abilities regarding spatial orientation and navigation, despite their small brain size. The behaviors that are based on spatial orientation differ dramatically between individual insect species according to their lifestyle and habitat. Central place foragers like bees and ants, for example, orient themselves in their surrounding and navigate back to the nest after foraging for food or water. Insects like some locust and butterfly species, on the other hand, use spatial orientation during migratory phases to keep a stable heading into a certain direction over a long period of time. In both scenarios, homing and long-distance migration, vision is the primary source for orientation cues even though additional features like wind direction, the earth’s magnetic field, and olfactory cues can be taken into account as well. Visual cues that are used for orientational purposes range from landmarks and the panorama to celestial cues. The latter consists in diurnal insects of the position of the sun itself, the sun-based polarization pattern and intensity and spectral gradient, and is summarized as sky-compass system. For a reliable sky-compass orientation, the animal needs, in addition to the perception of celestial cues, to compensate for the daily movement of the sun across the sky. It is likely that a connection from the circadian pacemaker system to the sky-compass network could provide the necessary circuitry for this time compensation.
The present thesis focuses on the sky-compass system of honeybees and locusts. There is a large body of work on the navigational abilities of honeybees from a behavioral perspective but the underlying neuronal anatomy and physiology has received less attention so far. Therefore, the first two chapters of this thesis reveals a large part of the anatomy of the anterior sky-compass pathway in the bee brain. To this end, dye injections, immunohistochemical stainings, and ultrastructural examinations were conducted. The third chapter describes a novel methodical protocol for physiological investigations of neurons involved in the sky-compass system using calcium imaging in behaving animals. The fourth chapter of this thesis deals with the anatomical basis of time compensation in the sky-compass system of locusts. Therefore, the ultrastructure of synaptic connections in a brain region of the desert locust where the contact of both systems could be feasible has been investigated
Evolutionary Computation 2020
Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms
Geoinformatics in Citizen Science
The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science
Research and Creative Activity, July 1, 2020-June 30, 2021: Major Sponsored Programs and Faculty Accomplishments in Research and Creative Activity, University of Nebraska-Lincoln
Foreword by Bob Wilhelm, Vice Chancellor for Research and Economic Development, University of Nebraska-Lincoln:
This booklet highlights successes in research, scholarship and creative activity by University of Nebraska–Lincoln faculty during the fiscal year running July 1, 2020, to June 30, 2021.
It lists investigators, project titles and funding sources on major grants and sponsored awards received during the year; fellowships and other recognitions and honors bestowed on our faculty; books and chapters published by faculty; performances, exhibitions and other examples of creative activity; patents and licensing agreements issued; National Science Foundation I-CORPS teams; and peer-reviewed journal articles and conference presentations. In recognition of the important role faculty have in the undergraduate experience at Nebraska, this booklet notes the students and mentors participating in the Undergraduate Creative Activities and Research Experience (UCARE) and the First-Year Research Experience (FYRE) programs.
While metrics cannot convey the full impact of our work, they are tangible measures of growth. A few achievements of note:
• UNL achieved a record 372 million.
• Industry sponsorship supported 6.48 million in licensing income.
I applaud the Nebraska Research community for its determination and commitment during a challenging year. Your hard work has made it possible for our momentum to continue growing.
Our university is poised for even greater success. The Grand Challenges initiative provides a framework for developing bold ideas to solve society’s greatest issues, which is how we will have the greatest impact as an institution. Please visit research.unl.edu/grandchallenges to learn more. We’re also renewing our campus commitment to a journey of anti-racism and racial equity, which is among the most important work we’ll do.
I am pleased to present this record of accomplishments.
Contents
Awards of 1 Million to 250,000 to 250,000 or More
Arts and Humanities Awards of 249,999
Arts and Humanities Awards of 49,999
Patents
License Agreements
National Science Foundation Innovation Corps Teams
Creative Activity
Books
Recognitions and Honors
Journal Articles 105 Conference Presentations
UCARE and FYRE Projects
Glossar
Real time tracking using nature-inspired algorithms
This thesis investigates the core difficulties in the tracking field of computer vision. The aim is to develop a suitable tuning free optimisation strategy so that a real time tracking could be achieved. The population and multi-solution based approaches have been applied first to analyse the convergence behaviours in the evolutionary test cases. The aim is to identify the core misconceptions in the manner the search characteristics of particles are defined in the literature. A general perception in the scientific community is that the particle based methods are not suitable for the real time applications. This thesis improves the convergence properties of particles by a novel scale free correlation approach. By altering the fundamental definition of a particle and by avoiding the nostalgic operations the tracking was expedited to a rate of 250 FPS.
There is a reasonable amount of similarity between the tracking landscapes and the ones generated by three dimensional evolutionary test cases. Several experimental studies are conducted that compares the performances of the novel optimisation to the ones observed with the swarming methods. It is therefore concluded that the modified particle behaviour outclassed the traditional approaches by huge margins in almost every test scenario
13th Annual Focus on Creative Inquiry Poster Forum Program
The Focus on Creative Inquiry (FoCI) Poster Forum is an annual event in which CI teams can present their research and project accomplishments through poster and interactive displays. FoCI is a celebration of student and mentor collaboration and accomplishments! FoCI is a great venue for students to develop and hone their communication skills