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Online services on the Internet are increasing day by day, and in parallel, the number of cyber-attacks is rapidly increasing. These attacks are not always about data theft, but they can cause severe damage by denial of service attacks. Intrusion Prevention System products that many organizations use at the border of their enterprise networks are not strong enough to protect against DoS attacks. The typical way to mitigate such attacks is to get support from a service provider. However, a service provider only provides solutions for the traffic originating from itself. If the source of attack is in another ISP domain, it is possible to inform that ISP via phone or e-mail. As a result, the source of the attack is blocked by the manual intervention of the service provider whose domain hosts it. Border Gateway Protocol (BGP) based solutions are also available for automating a blocking system, but not all enterprise networks support BGP. In this research, we have developed a centralized automation solution for software defined network (SDN) environments that is capable of preventing cyber-attacks at the source of attack. This solution does not require any BGP support. Non-SDN environments can also use this attack mitigation and notification system. In the long run, we may use this system to create a national protection shield in order to mitigate Cybersecurity attacks. [ABSTRACT FROM AUTHOR]

Complementary resistive switches (CRSs) are suggested as an alternative to one-cell memristor memories to decrease leakage currents. However, their sensing is more difficult and complex than one-cell memristor memories. A method has been given for sensing their state using only DC voltages in the literature. However, in this strategy, sensing one of the logic states results in the destruction of the state and the destroyed state must be written again. To the best of our knowledge, a circuit with this sensing strategy does not exist in the literature yet. In this paper, such a circuit employing this method, which is able to read the CRS cells and able to reconstruct their data if the data are destroyed, is given. A new CRS model is also constructed in this paper and used for simulations to verify the operation of the circuit. The circuit is simulated using Simulink. We expect this circuit implementation to find use in the design and testing of CRS cells. [ABSTRACT FROM AUTHOR]

Aim: To investigate whether electroencephalographic (EEG) frequency bands are applicable in distinguishing abnormal respiratory events such as obstructive apnea and hypopnea in patients with sleep apnea. Materials and methods: The polysomnographic recordings of 20 patients were examined retrospectively. EEG record segments were taken from C4-A1 and C3-A2 channels and were analyzed with software that uses digital signal processing methods, developed by the study team. Percentage values of delta, theta, alpha, and beta frequency bands were evaluated through discriminant and receiver-operator curve (ROC) analysis to distinguish between apneas and hypopneas. Results: For the C4-A1 channel, delta (%) provided the highest discriminative value (AUC = 0.563; P < 0.001); on the other hand, alpha (%) gave the lowest discriminative value (AUC = 0.519; P = 0.041). Likewise, whereas for the C3-A2 channel delta (%) gave the highest discriminative value (AUC = 0.565; P < 0.001), alpha produced the lowest discriminative value (AUC = 0.501; P = 0.943). Conclusion: As a result of discriminant analysis, the accurate classification rate of hypopneas was 44.8% and the accurate classification of obstructive apneas was 63.5%. Of the 4 frequency bands, the most significant was delta. The predictive values were not at significance level. [ABSTRACT FROM AUTHOR]