Knowledge growing is one of intelligence characteristics possessed by human brain. In this paper we review some fundamental theories that are appropriate for emulating this kind of intelligence in order to develop an intelligent system in Artificial Intelligence (AI) field, called brain-inspired Knowledge-Growing System (KGS). The development of this system is approached from various fields, namely psychological, mathematical, social, and electrical engineering and informatics fields. Based on the review results, we have built this system along with mechanism for growing the knowledge that consists of a model of Human Inference System (HIS), Sense-Inference-Decide and Act (SIDA) cycle, and the mathematical formulation for growing the knowledge called Observation Multi-time Arwin-Adang-Aciek-Sembiring (OMA3S) information-inferencing fusion method. In conclusion, brain-inspired KGS is a cognitive agent which is equipped with knowledge growing mechanism as its intelligent characteristic.

This paper present a particle filter for mobile robot localization also known as Monte Carlo Localization (MCL) to solve the localization problem of autonomous mobile robot. A new resampling mechanism is proposed. This new resampling mechanism enables the particle filter to converge quicker and more robust to kidnaping problem. This particle filter is simulated in MATLAB and also experimented physically using a simple autonomous mobile robot built with Lego Mindstorms NXT with 3 ultrasonic sonar and RWTH Mindstorms NXT Toolbox for MATLAB to connect the robot to MATLAB. The particle filter with the new resampling algorithm can perform very well in thesimulation as well as in physical experiments.

Cryptography is a science of creating a secret message and it is constantly developed. The development consists of attacking and defending the cryptography itself. Power analysis is one of many Side-Channel Analysis (SCA) attack techniques. Power analysis is an attacking technique that uses the information of a cryptographic hardware's power consumption. Power analysis is carried on by utilizing side-channel information to a vulnerability in a cryptographic algorithm. Power analysis also uses a mathematical model to recover the secret key of the cryptographic device. This research uses design research methodology as a research framework started from research clarification to descriptive study. In this research, power analysis attack is implemented to three symmetrical cryptographic algorithms: DES (Data Encryption Standard), AES (Advanced Encryption Standard), and BC3 (Block Cipher 3). The attack has successfully recovered 100% of AES secret key by using 500 traces and 75% DES secret key by using 320 traces. The research concludes that the power analysis attack using Pearson Correlation Coefficient (PCC) method produces more optimal result compared to a difference of means method.

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