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Embedded processors are closely integrated into the fabric of everyday life, such as cars and cell phones. These embedded processors enable new features; however, the features increase complexity. The steady increase in complexity results in bugs, which require software updates to fix. This leads to the question "How do we securely use (potentially) compromised devices or devices we don't trust?" Briefing examines the attacker model and how to ensure code integrity.

The idea of exploring the multidimensional characteristics biocomputing deals with involves a multilevel protein logic interaction with hybrid analog and digital systems (bio/digital/analog systems). In the protein biocomputing world, all models are nonlinear exponential in nature. These nonlinear systems are linearized by boundary limited frequency, time response and dimensional ranges. The protein model and its correct development is probably the most difficult aspect for biocomputing issues. These future computing devices will be chemical sensors, fluidic computer systems, optical switches, nanoactuators, self-repairing computing systems, nanorobots and reusable analog components. Noise reduction techniques for these systems involve spiking neural network techniques for data extraction. Reusable Analog Integrated Circuit Components are needed for hardware signal processing and for System-on-A-Chip (SoC) Integration. These include: Microwave Operational Amplifier(s); Switched Capacitor Filters; and Voltage References. During this research period, the analog design efforts have been focused on re-configurable microwave Op-Amp. A prototype 0.18 CMOS SOI design structure fort RF high-gain op-amp was submitted for prototype implementation.

The idea of exploring the multidimensional characteristics biocomputing deals with involves a multilevel protein logic interaction with hybrid analog and digital systems (bio/digital/analog systems). In the protein biocomputing world, all models are nonlinear exponential in nature. These nonlinear systems are linearized by boundary limited frequency, time response and dimensional ranges. The protein model and its correct development is probably the most difficult aspect for biocomputing issues. These future computing devices will be chemical sensors, fluidic computer systems, optical switches, nanoactuators, self-repairing computing systems, nanorobots and reusable analog components. Noise reduction techniques for these systems involve spiking neural network techniques for data extraction. Reusable Analog Integrated Circuit Components are needed for hardware signal processing and for System-on-A-Chip (SoC) Integration. These include: Microwave Operational Amplifier(s); Switched Capacitor Filters; and Voltage References. During this research period, the analog design efforts have been focused on re-configurable microwave Op-Amp. A prototype 0.18 CMOS SOI design structure fort RF high-gain op-amp was submitted for prototype implementation.