ARTIFICIAL NEURAL SYSTEM FOR REAL-TIME FLOW CYTOMETRY ANALYSIS IN OCEAN RESEARCH

RESEARCH IN PARALLEL PROCESSING ARCHITECTURES BASED ON KTAADN, INC.'S EXPERTISE IN ARTIFICIAL NEURAL NETWORKS IS PROPOSED TO ANSWER THE NEEDS OF THE COMMUNITY OF RESEARCHERSUSING OCEAN-GOING FLOW CYTOMETRY. FLOW CYTOMETRY, WIDELY USED IN MEDICAL RESEARCH AND DIAGNOSIS, HAS REVOLUTIONIZED OCEAN MICROBIOLOGICAL RESEARCH SINCE ITS INTRODUCTION, AND CHANGED DRAMATICALLY OUR UNDERSTANDING OF THE INTERPLAY OF OCEAN FOOD CHAINS AND BIOMASS PRODUCTION. HOWEVER, THIS NEWTECHNIQUE REQUIRES THE STORAGE AND ANALYSIS OF ENORMOUS QUANTITIES OF DATA, WHICH CURRENTLY ARE ANALYZED ON SHORE, WHEN THERE IS NO CHANCE TO RESPOND TO INTERESTING OBSERVATIONS. THE DEVELOPMENT OF REAL-TIME DATA ANALYSIS HARDWARE AND SOFTWARE WOULD SIGNIFICANTLY EASE THE BURDEN OFANALYSIS OF THE DATA AND ACCELERATE RESEARCH INTO THE LIFE PROCESSES IN THE OCEANS.