Fully homomorphic encryption (FHE) is a powerful scheme that can be applied to perform computations directly on encrypted data for ensuring the security of cloud computing. Using the concept of aggregate plaintext, this paper explores how to optimize the compare-and-swap operation, commonly used for sorting and searching in cloud computing, for FHE data. The resulting performance is optimized by properly arranging the operand locations, corresponding to the desired plaintext slots, and then scheduling a sequence of fundamental homomorphic operations designed to accomplish the targeted operation. Moreover, the hypercube plaintext slot structure is considered to efficiently manipulate the required shift operation and merge multiple operands in an aggregate plaintext. Analytical results show that the number of homomorphic multiplication and shift operations needed in the proposed compare-and-swap operation are logn + 4 and 2logn + 1, respectively, for n-bit data, which is at least 16 times faster than related works for n = 64. Applying the proposed scheme can not only reduce the size of required FHE data, but also improve the total computation time of the chosen operation.

Capacitor matching influences linearity performance, which is a critical measure of analog-to-digital converters (ADCs). Various placement techniques have been proposed to eliminate both systematic and random mismatches of capacitor pairs. However, a placement technique that eliminates capacitor mismatches may not result in good linearity performance for successive-approximation-register ADCs because their linearity performance is related to the accuracy of their binary-weighted continued ratio. This paper addresses the critical problem of placement estimation based on ratio mismatch M, overall correlation coefficient L, and performance metrics. A low M and a high L value do not imply higher linearity performance. Therefore, we propose a partition-centering-based symmetry placement algorithm for the layout considering parasitic capacitance matching. The experimental results show that the proposed placement approach can achieve higher linearity performance and a shorter placement generation time compared with the conventional approach.

The performance of many switched-capacitor analog integrated circuits, such as analog-to-digital converters (ADCs) and sample and hold circuits, is directly related to their accurate capacitance ratios. In general, capacitor mismatch can result from two sources of errors: random mismatch and systematic mismatch. Paralleling unit capacitance (UC) with a common-centroid structure can alleviate the random mismatch errors. The complexity of generating an optimal solution to the UC placement problem is extremely high, let alone if both placement and routing problems are to be optimized simultaneously. This article evaluates the performance of the UC placement generated in an existing work and proposes an alternative UC placement to achieve optimal ratio mismatch M and better linearity performance of SAR ADC design. Results show that the proposed UC placement achieves a ratio mismatch of M = 0.695, the effective number of bits ENOB = 8.314 bits, and the integral nonlinearity INL = 0.816 LSB (least significant bits) for a 9-bit SAR ADC design.

Yield is defined as the probability that the circuit under consideration meets with the design specification within the tolerance. Placement with higher correlation coefficients has fewer mismatches and lower variation of capacitor ratio, thus achieving higher yield performance. This study presents a new optimization criterion that quickly determines if the placement is optimal. The optimization criterion leads to the development of the concepts of C-entries and partitioned subarrays which can significantly reduce the searching space for finding the optimal/near-optimal placements on a sufficiently large array size.

This paper proposes the architecture of learning companion agent with facial expression of emotion. Based on ABC and ToK architecture, the emotion agent architecture contains five modules to realize the interaction in the world. A particular part of this research is the transition between emotion space in emotion module and facial expression space in facial expression module. Using this transition and those five modules, a small experiment Web site with emotion agent demonstrates the facial expression of the agent and its emotion tracks.