Suggestopedic mobile language learning

The use of suggestopedic teaching methods has been shown to be effective in the domain of language learning. Suggestopaedia is a classroom teaching method that employs certain strategies to enable learners to relax in order to enable more effective learning both consciously and subconsciously. The use of mobile technologies to support language learning has also become very useful and popular. This paper proposes the amalgamation of the two approaches to enable a mobile suggestopedic platform and demonstrates empirical evidence linked to the success of this approach on languge learning. The design of a Suggestopedic mobile language learning app is discussed together with different target groups of learners that can benefit from this type of teaching. Design, development and evaluation of this app forms our future work

Representations of hom-Lie algebras

In this paper, we study representations of hom-Lie algebras. In particular, the adjoint representation and the trivial representation of hom-Lie algebras are studied in detail. Derivations, deformations, central extensions and derivation extensions of hom-Lie algebras are also studied as an application.Comment: 16 pages, multiplicative and regular hom-Lie algebras are used, Algebra and Representation Theory, 15 (6) (2012), 1081-109

Schwarzschild Field of a Proper Time Oscillator

In this paper, we show that an oscillator in proper time can mimic a point mass at rest in general relativity. The spacetime outside this proper time oscillator is static and satisfies the Schwarzschild solution.Comment: 12 pages. Published versio

Optimal Attack against Cyber-Physical Control Systems with Reactive Attack Mitigation

This paper studies the performance and resilience of a cyber-physical control system (CPCS) with attack detection and reactive attack mitigation. It addresses the problem of deriving an optimal sequence of false data injection attacks that maximizes the state estimation error of the system. The results provide basic understanding about the limit of the attack impact. The design of the optimal attack is based on a Markov decision process (MDP) formulation, which is solved efficiently using the value iteration method. Using the proposed framework, we quantify the effect of false positives and mis-detections on the system performance, which can help the joint design of the attack detection and mitigation. To demonstrate the use of the proposed framework in a real-world CPCS, we consider the voltage control system of power grids, and run extensive simulations using PowerWorld, a high-fidelity power system simulator, to validate our analysis. The results show that by carefully designing the attack sequence using our proposed approach, the attacker can cause a large deviation of the bus voltages from the desired setpoint. Further, the results verify the optimality of the derived attack sequence and show that, to cause maximum impact, the attacker must carefully craft his attack to strike a balance between the attack magnitude and stealthiness, due to the simultaneous presence of attack detection and mitigation

Modeling and Detecting False Data Injection Attacks against Railway Traction Power Systems

Modern urban railways extensively use computerized sensing and control technologies to achieve safe, reliable, and well-timed operations. However, the use of these technologies may provide a convenient leverage to cyber-attackers who have bypassed the air gaps and aim at causing safety incidents and service disruptions. In this paper, we study false data injection (FDI) attacks against railways' traction power systems (TPSes). Specifically, we analyze two types of FDI attacks on the train-borne voltage, current, and position sensor measurements - which we call efficiency attack and safety attack -- that (i) maximize the system's total power consumption and (ii) mislead trains' local voltages to exceed given safety-critical thresholds, respectively. To counteract, we develop a global attack detection (GAD) system that serializes a bad data detector and a novel secondary attack detector designed based on unique TPS characteristics. With intact position data of trains, our detection system can effectively detect the FDI attacks on trains' voltage and current measurements even if the attacker has full and accurate knowledge of the TPS, attack detection, and real-time system state. In particular, the GAD system features an adaptive mechanism that ensures low false positive and negative rates in detecting the attacks under noisy system measurements. Extensive simulations driven by realistic running profiles of trains verify that a TPS setup is vulnerable to the FDI attacks, but these attacks can be detected effectively by the proposed GAD while ensuring a low false positive rate.Comment: IEEE/IFIP DSN-2016 and ACM Trans. on Cyber-Physical System

Reducing standby power applied to SR forward converters with transient load response considered

[[abstract]]Up to the present, how to process standby power is getting more and more attractive. Therefore, in this paper, hybrid methods, including duty cycle detection and current detection, are applied to controlling operation states of the synchronous rectification (SR) forward converter, so as to reduce standby power as minimum as possible. At the same time, the performance of the transient load response due to a step load change from no/full to full/no load is also taken into consideration. The proposed approach is described in detail and verified by some simulation and experimental results.[[conferencetype]]國際[[conferencedate]]20040725~20040728[[conferencelocation]]Hiroshima, Japa