This paper presents the approach of the quantum complex-valued backpropagation neural network or QCBPN. The challenge of our research is the expected results fiom the development of the quantum neural network using complex-valued backpropagation learning algorithm to solve classification problems. The concept of QCBPN emerged fiom the quantum circuit neural network research and the complex-valued backpropagation algorithm. We found that complex value and the quantum states share some natural representation suitable for the parallel computation. The quantum circuit neural network provides a qubit-like neuron model based on quantum mechanics with quantum backpropagationlearning rule, while the complex-valued backpropagation algorithm modifies standard backpropagation algorithm to learn complex number pattem in a natural way. The quantum complex-valued neuron model and the QCBPN learning algorithm are described. Finally, the realization of the QCBPN is exploited with a simple pattem recognition problem.

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Dissemination of information in today's digital lifestyle has grown beyond prints, multimedia contents are no longer luxurious elements but necessary components. Combined with an advanced navigation system on Android-based mobile devices and augmented reality technology, we achieve a contextaware self-guided application that not only assists users navigating an unknown territory but also delivers facts about places they are visiting as well as living and non-living things they are encountering. Applying such a system to zoos, the largest living classrooms in existance, while incorporating cartoon-like kids' friendly interfaces and games, we have developed a portable educational gadget. Our application, named ZooEduGuide, is designed to effectively attract and motivate young children and teenagers to learn about animals and wildlife along with ecological footprints. It encourages their love for animals and raises their awareness for environmental conservation as today, more than ever before, there is an urgent need to actively protect wildlife at a global scale. Enhancing zoo experience with ZooEduGuide, a planned field-trip at the zoo could be personalized. Furthermore, the flexibility and generalizability of our system allows local zoos to customize their maps and to dynamically schedule show events. At the same time, many zoos across the country can share common information and news through a centralized on-board database managed by the national zoo organization.

Abstract-Computational thinking sits at the core of every engineering and computing related discipline. It has increasingly emerged as its own subject in all levels of education. It is a powerful cornerstone for cognitive development, creative problem solving, algorithmic thinking and designs, and programming. How to effectively teach computational thinking skills poses real challenges and creates opportunities. Targeting entering computer science and engineering undergraduates, we resourcefully integrate elements from artificial intelligence (AI) into introductory computing courses. In addition to comprehension of the essence of computational thinking, practical exercises in AI enable inspirations of collaborative problem solving beyond abstraction, logical reasoning, critical and analytical thinking. Problems in machine intelligence systems intrinsically connect students to algorithmic oriented computing and essential mathematical foundations. Beyond knowledge representation, AI fosters a gentle introduction to data structures and algorithms. Focused on engaging mental tool, a computer is never a necessity. Neither coding nor programming is ever required. Instead, students enjoy constructivist classrooms designed to always be active, flexible, and highly dynamic. Learning to learn and reflecting on cognitive experiences, they rigorously construct knowledge from collectively solving exciting puzzles, competing in strategic games, and participating in intellectual discussions.