Reliability Analysis of Electric Power Systems Considering Cyber Security

The new generation of the electric power system is the modern smart grid which is essentially a cyber and physical system (CPS). Supervisory control and data acquisition (SCADA)/energy management system (EMS) is the key component of CPS, which is becoming the main target of both external and insider cyberattacks. Cybersecurity of the SCADA/EMS system is facing big challenges and influences the reliability of the electric power system. Characteristics of cyber threats will impact the system reliability. System reliability can be influenced by various cyber threats with different attack skill levels and attack paths. Additionally, the change of structure of the target system may also result in the change of the system reliability. However, very limited research is related to the reliability analysis of the electric power system considering cybersecurity issue. A large amount of mathematical methods can be used to quantify the cyber threats and simulation processes can be applied to build the reliability analysis model. For instance, to analyze the vulnerabilities of the SCADA/EMS system in the electric power system, Bayesian Networks (BNs) can be used to model the attack paths of cyberattacks on the exploited vulnerabilities. The mean time-to-compromise (MTTC) and mean time-to-failure (MTTF) based on the Common Vulnerability Scoring System (CVSS) can be applied to characterize the properties of cyberattacks. What’s more, simulation approaches like non-sequential or sequential Monte Carlo Simulation (MCS) is able to simulate the system reliability analysis and calculate the reliability indexes. In this thesis, reliability of the SCADA/EMS system in the electric power system considering different cybersecurity issues is analyzed. The Bayesian attack path models of cyberattacks on the SCADA/EMS components are built by Bayesian Networks (BNs), and cyberattacks are quantified by its mean time-to-compromise (MTTC) by applying a modified Semi-Markov Process (SMP) and MTTC models. Based on the IEEE Reliability Test System (RTS) 96, the system reliability is analyzed by calculating the electric power system reliability indexes like LOLP and EENS through MCS. What’s more, cyberattacks with different lurking strategies are considered and analyzed. According to the simulation results, it shows that the system reliability of the SCADA/EMS system in the electric power system considering cyber security is closely related to the MTTC of cyberattacks, which is influenced by the attack paths, attacking skill levels, and the complexity of the target structure. With the increase of the MTTC values of cyberattacks, LOLP values decrease, which means that the reliability of the system is better, and the system is safer. In addition, with the difficulty level of lurking strategies of cyberattacks getting higher and higher, though the LOLP values of scenarios don’t increase a lot, the EENS values of the corresponding scenarios increase dramatically, which indicates that the system reliability is more unpredictable, and the cyber security is worse. Finally, insider attacks are discussed and corresponding LOLP values and EENS values considering lurking behavior are estimated and compared. Both LOLP and EENS values dramatically increase owing to the insider attacks that result in the lower MTTCs. This indicates that insider attacks can lead to worse impact on system reliability than external cyber attacks. The results of this thesis may contribute to the establishment of perfect countermeasures against with cyber attacks on the electric power system

Information recovery in the Hayden-Preskill protocol

We revisit information retrieval from evaporating black holes in the Hayden-Preskill protocol, treating the black hole dynamics as Haar-random. We compute, down to the first exponentially suppressed terms, all integer-indexed R\'enyi mutual informations between a black hole, its radiation, and a reference that catalogues Alice's diaries. We find that dropping a diary into a young black hole effectively delays the Page time. We also compute the radiation : diary reflected R\'enyi entropies, and identify a technical reason why they cannot be continued to the reflected entropy by the replica trick.Comment: 24 pages plus appendice

Empirical Investigation of the Relationship among Profitability, Market Structure and Efficiency in Indian Banking Sector

After the employment of several reforms that happened mainly in 1990s, the face of the Indian banking sector has been impressively changed. The purpose of these policies, such as deregulation and lowering entry barriers, was to enhance the efficiency, flexibility and the level of competition in the Indian banking sectors. Therefore, this study aims to figure out what is the relationship among market structure, efficiency and profitability in Indian banking sector from 2009 to 2014, after the reforms in 1990s. Four hypotheses – Structure-Conduct Performance (SCP) hypothesis, Relative Market Power (RMP) hypothesis, X-efficiency (ESX) hypothesis, and the Scale-efficiency (ESS) hypothesis, are tested by using panel data regression. Moreover, the necessary condition for efficient structure hypotheses and the ‘quiet life’ hypothesis are further tested. Estimation of these models shows some supports for the SCP hypothesis during the researched period. The X-efficiency hypothesis is preliminarily supported, but there is no evidence to support the necessary condition. Thus for the Indian banking sector, high profits could obtained from the higher level of market concentration. Overall, the stronger role of competition policy might be suggested for the Indian government to better development of its banking industry

Orthogonal Spatial Coding with Stimulated Parametric Down-Conversion

Orthogonal optical coding is widely used in classical multiuser communication networks. Using the phase conjugation property of stimulated parametric down-conversion, we extend the current orthogonal optical coding scheme to the spatial domain to encode and decode image information. In this process, the idler beam inherits the complex conjugate of the field information encoded in the seed beam. An encoding phase mask introduced to the input seed beam blurs the image transferred to the idler. The original image is restored by passing the coded transferred image through a corrective phase mask placed in the momentum space of the idler beam. We expect that this scheme can also inspire new techniques in aberration cancellation and frequency conversion imaging

Situating expectancies and subjective task values across grade levels, domains, and countries : A network approach

In their recently renamed theory, situated expectancy-value theory (SEVT), Eccles and Wigfield (2020) emphasized the importance of situations in influencing individuals’ motivational beliefs and academic choices. Adopting a novel approach—network analysis—this study aimed to examine how situations may impact the associations among expectancies, subjective task values, and achievement from a holistic perspective. In this study, situations were operationalized as grade levels (i.e., 6th –9th grade), subject domains (i.e., language arts and math), and countries (i.e., Finland and Germany). Adolescents from Finland (N = 4,062) and Germany (N = 449) were included in the study. Results showed that, overall, the networks are mostly subject bound, yearly varied, and country specific, supporting the situative nature of SEVT. We also found that expectancies were consistently the closest motivational beliefs to achievement, whereas utility values were the least close, implying that expectancies, not utility, might be the most desirable intervention targets for achievement improvement.Peer reviewe

Lumen contour segmentation in ivoct based on n-type cnn

Automatic segmentation of lumen contour plays an important role in medical imaging and diagnosis, which is the first step towards the evaluation of morphology of vessels under analysis and the identification of possible atherosclerotic lesions. Meanwhile, quantitative information can only be obtained with segmentation, contributing to the appearance of novel methods which can be successfully applied to intravascular optical coherence tomography (IVOCT) images. This paper proposed a new end-to-end neural network (N-Net) for the automatic lumen segmentation, using multi-scale features based deep neural network, for IVOCT images. The architecture of the N-Net contains a multi-scale input layer, a N-type convolution network layer and a cross-entropy loss function. The multi-scale input layer in the proposed N-Net is designed to avoid the loss of information caused by pooling in traditional U-Net and also enriches the detailed information in each layer. The N-type convolutional network is proposed as the framework in the whole deep architecture. Finally, the loss function guarantees the degree of fidelity between the output of proposed method and the manually labeled output. In order to enlarge the training set, data augmentation is also introduced. We evaluated our method against loss, accuracy, recall, dice similarity coefficient, jaccard similarity coefficient and specificity. The experimental results presented in this paper demonstrate the superior performance of the proposed N-Net architecture, comparing to some existing networks, for enhancing the precision of automatic lumen segmentation and increasing the detailed information of edges of the vascular lumen

Empirical Investigation of the Relationship among Profitability, Market Structure and Efficiency in Indian Banking Sector

After the employment of several reforms that happened mainly in 1990s, the face of the Indian banking sector has been impressively changed. The purpose of these policies, such as deregulation and lowering entry barriers, was to enhance the efficiency, flexibility and the level of competition in the Indian banking sectors. Therefore, this study aims to figure out what is the relationship among market structure, efficiency and profitability in Indian banking sector from 2009 to 2014, after the reforms in 1990s. Four hypotheses – Structure-Conduct Performance (SCP) hypothesis, Relative Market Power (RMP) hypothesis, X-efficiency (ESX) hypothesis, and the Scale-efficiency (ESS) hypothesis, are tested by using panel data regression. Moreover, the necessary condition for efficient structure hypotheses and the ‘quiet life’ hypothesis are further tested. Estimation of these models shows some supports for the SCP hypothesis during the researched period. The X-efficiency hypothesis is preliminarily supported, but there is no evidence to support the necessary condition. Thus for the Indian banking sector, high profits could obtained from the higher level of market concentration. Overall, the stronger role of competition policy might be suggested for the Indian government to better development of its banking industry

Toxic Effects of Tetracycline and Its Removal by the Freshwater Microalga Chlorella pyrenoidosa

The prevalence of tetracycline (TC) in aquatic environments has raised increasing concern due to its high ecotoxicology risk. The application of microalgae in the removal of antibiotics is a competitive alternative technology. However, the removal mechanism of TC by microalgae and its correlation with the ecotoxic response of microalgae are still not clear. In this study, the ecotoxicity of TC (0.5–10 mg L−1) and its removal by the freshwater alga Chlorella pyrenoidosa were investigated. The results show that TC has significant inhibitory effects on microalgal growth, photosynthetic pigment, and photosynthetic efficiency, with maximum inhibition rates of 49.68%, 62.54%, and 48.08%, respectively. However, the growth inhibition and photosynthesis impairment caused by TC seems to be reversible, as reflected by the decreased inhibition rates with prolonged exposure time. The simultaneous increases in the activities of superoxide dismutase (9.69–23.53%) and peroxidase (15.15–110.92%) and the contents of glutathione (17.62–64.17%) and malondialdehyde (25.16–35.25%) suggest that TC causes moderate oxidative stress. C. pyrenoidosa exhibits high removal efficiency (91.44–95.14%) for TC after 48 h of exposure with short half-lives of 11.31–13.48 h. Biodegradation (56.86–64.62%) is the primary removal mechanism of TC, accompanied by the abiotic process (24.68–40.97%), bioaccumulation (1.95–10.97%), and bioadsorption (0.09–0.38%). These findings demonstrate the toxicity resistance and high removal capacity of C. pyrenoidosa to TC, highlighting its potential application in the remediation of TC-contaminated water

Facial Expression Recognition Based on Dual-Channel Fusion with Edge Features

In the era of artificial intelligence, accomplishing emotion recognition in human–computer interaction is a key work. Expressions contain plentiful information about human emotion. We found that the canny edge detector can significantly help improve facial expression recognition performance. A canny edge detector based dual-channel network using the OI-network and EI-Net is proposed, which does not add an additional redundant network layer and training. We discussed the fusion parameters of α and β using ablation experiments. The method was verified in CK+, Fer2013, and RafDb datasets and achieved a good result

An Improved Sparrow Search Algorithm for Solving the Energy-Saving Flexible Job Shop Scheduling Problem

Due to emerging requirements and pressures related to environmental protection, manufacturing enterprises have expressed growing concern for adopting various energy-saving strategies. However, environmental criteria were usually not considered in traditional production scheduling problems. To overcome this deficiency, energy-saving scheduling has drawn more and more attention from academic scholars and industrial practitioners. In this paper, an energy-saving flexible job shop scheduling problem (EFJSP) is introduced in accordance with the criterion of optimizing power consumption and processing costs simultaneously. Since the classical FJSP is strongly NP-hard, an Improved Sparrow Search Algorithm (ISSA) is developed for efficiently solving the EFJSP. In the ISSA, a Hybrid Search (HS) method is used to produce an initial high-quality population; a Quantum Rotation Gate (QRG) and a Sine–Cosine Algorithm (SCA) are integrated to intensify the ability of the ISSA to coordinate exploration and exploitation; the adaptive adjustment strategy and Variable Neighborhood Search (VNS) are applied to strengthen diversification of the ISSA to move away from local optima. Extensive computational experiments validate that the ISSA outperforms other existing algorithms in solving the EFJSP due to the advantages of intensification and diversification mechanisms in the ISSA.</p