A generic method to construct new customized-shaped haotic systems using the relative motion concept

Constructing chaotic systems tailored for each particular real-world application has been a long-term research desideratum. We report a solution for this problem based on the concept of relative motion. We investigate the periodic motion on a closed contour of a coordinate frame in which a chaotic system evolves. By combining these two motions (periodic on a close contour and chaotic) new customized shape trajectories are acquired. We demonstrate that these trajectories obtained in the stationary frame are also chaotic and, moreover, conserve the Lyapunov exponents of the initial chaotic system. Based on this finding we developed an innovative method to construct new chaotic systems with customized shapes, thus fulfilling the requirements of any particular application of chaos

Path Planning Algorithm based on Arnold Cat Map for Surveillance UAVs

During their task accomplishment, autonomous unmanned aerial vehicles are facing more and more threats coming from both ground and air. In such adversarial environments, with no a priori information about the threats, a flying robot in charge with surveilling a specified 3D sector must perform its tasks by evolving on misleading and unpredictable trajectories to cope with enemy entities. In our view, the chaotic dynamics can be the cornerstone in designing unpredictable paths for such missions, even though this solution was not exploited until now by researchers in the 3D context. This paper addresses the flight path-planning issue for surveilling a given volume in adversarial conditions by proposing a proficient approach that uses the chaotic behaviour exhibited by the 3D Arnold’s cat map. By knowing the exact location of the volume under surveillance before take-off, the flying robot will generate the successive chaotic waypoints only with onboard resources, in an efficient manner. The method is validated by simulation in a realistic scenario using a detailed Simulink model for the X-4 Flyer quadcopter

Co-Occurrence-Based Double Thresholding Method for Research Topic Identification

Identifying possible research gaps is a main step in problem framing, however it is increasingly tedious and expensive considering the continuously growing amount of published material. This situation suggests the critical need for methodologies and tools that can assist researchers in their selection of future research topics. Related work mostly focuses on trend analysis and impact prediction but less on research gap identification. This paper presents our first approach in automated identification of feasible research gaps by using a double-threshold procedure to eliminate the research gaps that are currently difficult to study or offer little novelty. Gaps are then found by extracting subgraphs for the less-frequent co-occurrences and correlations of key terms describing domains. A case study applying the methodology for electronic design automation (EDA) domain is also discussed in the paper

Wireless Sensor Network Security Enhancement Using Directional Antennas: State of the Art and Research Challenges

Being often deployed in remote or hostile environments, wireless sensor networks are vulnerable to various types of security attacks. A possible solution to reduce the security risks is to use directional antennas instead of omnidirectional ones or in conjunction with them. Due to their increased complexity, higher costs and larger sizes, directional antennas are not traditionally used in wireless sensor networks, but recent technology trends may support this method. This paper surveys existing state of the art approaches in the field, offering a broad perspective of the future use of directional antennas in mitigating security risks, together with new challenges and open research issues