AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR SPECTRUM ALLOCATION IN COGNITIVE RADIO NETWORKS

The seriousness of the spectrum scarcity has increased dramatically due to the rapid increase of wireless services. The key enabling technology that can be viewed as a novel approach for utilizing the spectrum more efficiently is known as Cognitive Radio. Therefore, assigning the spectrum opportunistically to the unlicensed users without interfering with the licensed users, concurrently with maximizing the spectrum utilization is addressed as a major challenge problem in cognitive radio networks. In this paper, an improved metaheuristic optimization algorithm has been proposed to solve this problem that contingent on a graph coloring model. The proposed approach is a hybrid algorithm composed of a Particle Swarm Optimization algorithm with Random Neighborhood Search. The key objective function is maximizing the spectrum utilization in the cognitive radio networks with the subjected constraints. MATLAB R2021a was used for conducting the simulation. The proposed hybrid algorithm improved the system utilization by 1.23% compared to Particle Swarm Optimization algorithm, 5.57% compared to Random Neighborhood Search, 7.9% compared to Color Sensitive Graph Coloring algorithm, and 27.33% compared to Greedy algorithm. Moreover, the system performance was evaluated with various deployment scenarios of the primary users, secondary users, and channels for investigating the impact of varying these parameters on the system performance

A comprehensive survey on cultural algorithms

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Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement

Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method

SPICA:revealing the hearts of galaxies and forming planetary systems : approach and US contributions

How did the diversity of galaxies we see in the modern Universe come to be? When and where did stars within them forge the heavy elements that give rise to the complex chemistry of life? How do planetary systems, the Universe's home for life, emerge from interstellar material? Answering these questions requires techniques that penetrate dust to reveal the detailed contents and processes in obscured regions. The ESA-JAXA Space Infrared Telescope for Cosmology and Astrophysics (SPICA) mission is designed for this, with a focus on sensitive spectroscopy in the 12 to 230 micron range. SPICA offers massive sensitivity improvements with its 2.5-meter primary mirror actively cooled to below 8 K. SPICA one of 3 candidates for the ESA's Cosmic Visions M5 mission, and JAXA has is committed to their portion of the collaboration. ESA will provide the silicon-carbide telescope, science instrument assembly, satellite integration and testing, and the spacecraft bus. JAXA will provide the passive and active cooling system (supporting the

The Apertif Surveys:The First Six Months

Apertif is a new phased-array feed for the Westerbork Synthesis Radio Telescope (WSRT), greatly increasing its field of view and turning it into a natural survey instrument. In July 2019, the Apertif legacy surveys commenced; these are a time-domain survey and a two-tiered imaging survey, with a shallow and medium-deep component. The time-domain survey searches for new (millisecond) pulsars and fast radio bursts (FRBs). The imaging surveys provide neutral hydrogen (HI), radio continuum and polarization data products. With a bandwidth of 300 MHz, Apertif can detect HI out to a redshift of 0.26. The key science goals to be accomplished by Apertif include localization of FRBs (including real-time public alerts), the role of environment and interaction on galaxy properties and gas removal, finding the smallest galaxies, connecting cold gas to AGN, understanding the faint radio population, and studying magnetic fields in galaxies. After a proprietary period, survey data products will be publicly available through the Apertif Long Term Archive (ALTA, https://alta.astron.nl). I will review the progress of the surveys and present the first results from the Apertif surveys, including highlighting the currently available public data