Safety Protection Technology of Power Monitoring System Based on Feature Extraction Algorithm

The network security protection technology of power monitoring systems is of great significance. Aiming at the power network monitoring and protection technology problem, the paper proposes an active monitoring and protection strategy based on a feature extraction algorithm. The algorithm can calculate the transfer degree of security incidents based on evidence theory. First, the paper obtains a specific state transition diagram based on the security topology of a generalized random power communication network. Then, we analyze the relationship between power system information security and engineering security based on the system’s operating results and feature extraction algorithms. The experimental results demonstrate the rapid effectiveness of this method.

Fault-Tolerance by Resilient State Transition for Collaborative Cyber-Physical Systems

Collaborative Cyber-Physical Systems (CCPS) are systems where several individual cyber-physical systems collaborate to perform a single task. The safety of a single Cyber-Physical System (CPS) can be achieved by applying a safety mechanism and following standard processes defined in ISO 26262 and IEC 61508. However, due to heterogeneity, complexity, variability, independence, self-adaptation, and dynamic nature, functional operations for CCPS can threaten system safety. In contrast to fail-safe systems, where, for instance, the system leads to a safe state when an actuator shuts down due to a fault, the system has to be fail-operational in autonomous driving cases, i.e., a shutdown of a platooning member vehicle during operation on the road is unacceptable. Instead, the vehicle should continue its operation with degraded performance until a safe state is reached or returned to its original state in case of temporal faults. Thus, this paper proposes an approach that considers the resilient behavior of collaborative systems to achieve the fail-operational goal in autonomous platooning systems. First, we extended the state transition diagram and introduced additional elements such as failures, mitigation strategies, and safe exit to achieve resilience in autonomous platooning systems. The extended state transition diagram is called the Resilient State Transition Diagram (R-STD). Second, an autonomous platooning system’s perception, communication, and ego-motion failures are modeled using the proposed R-STD to check its effectiveness. Third, VENTOS simulator is used to verify the resulting resilient transitions of R-STD in a simulation environment. Results show that a resilient state transition approach achieves the fail-operational goal in the autonomous platooning system.

Quality Enhancement In A mm-Wave Multi-hop, Multi-Tier Heterogeneous 5G Network Architecture

Millimetre-wave ultra-dense high capacity networks by providing an important component of future 5G cellular systems, by providing extremely high capacity to end users. Disparate types of users coexist in such scenarios, which can make the heterogeneous network unfair in terms of allocation of resources. A mechanism is required for effective spectrum sharing and to achieve overall system fairness. In this paper, an analytical model is suggested, which is based on a two-dimensional Markov state-transition diagram, to help set the parameter values to control the issuance of resources in coexistence layouts. A restriction approach is further implemented to gain a fair balance of the Grade-of-Service for both user groups using the User Admission Control mechanism. The developed mechanism restricts access to various channel resources for users with complete choice to give a greater probability of access to different users with limited resource options. Various levels of restriction are investigated in order to offer a balanced low-blocking probability performance to both user groups in order to improve the overall network fairness. Also, the proposed approach could provide a precise level of Grade-of-Service guarantee for both the user groups if sufficient flexibility is available within the whole network. Our simulation results show that approximately 30% to 45% enhancement, in terms of grade of service (GoS), could be achieved in high to medium loads by restricting some users' flexibility.

Quantum cluster algorithm for data classification

We present a quantum algorithm for data classification based on the nearest-neighbor learning algorithm. The classification algorithm is divided into two steps: Firstly, data in the same class is divided into smaller groups with sublabels assisting building boundaries between data with different labels. Secondly we construct a quantum circuit for classification that contains multi control gates. The algorithm is easy to implement and efficient in predicting the labels of test data. To illustrate the power and efficiency of this approach, we construct the phase transition diagram for the metal-insulator transition of VO2, using limited trained experimental data, where VO2 is a typical strongly correlated electron materials, and the metallic-insulating phase transition has drawn much attention in condensed matter physics. Moreover, we demonstrate our algorithm on the classification of randomly generated data and the classification of entanglement for various Werner states, where the training sets can not be divided by a single curve, instead, more than one curves are required to separate them apart perfectly. Our preliminary result shows considerable potential for various classification problems, particularly for constructing different phases in materials.

Stochastic Intrusion Detection Game-Based Arrangement Using Controlled Markov Chain for Prevention of DoS and DDoS Attacks in Cloud

DoS (denial of service) assault is the most prevalent assault these days. It imposes a major risk to cybersecurity. At the point when this assault is propelled by numerous conveyed machines on a solitary server machine, it is called as a DDoS (distributed denial of service) assault. Additionally, DoS bypass on DHCP (dynamic host configuration protocol) server assault is a rising and famous assault in a system. The authors have proposed a stochastic intrusion detection game-based arrangement utilizing controlled Markov chain that figures the transition probabilities starting with one state then onto the next in a state transition diagram. At first, the authors have conjectured these assaults, and after that, they proposed a methodology that uses the idea of master and slave IPS (intrusion prevention system). This approach works well when mapped to these estimated assaults and accordingly helps in the recognition and counteractive action of these assaults in a cloud domain.

Synthesis of Scalable Single Length Cycle, Single Attractor Cellular Automata in Linear Time

This paper proposes the synthesis of single length cycle, single attractor cellular automata (SACAs) for arbitrary length. The n-cell single length cycle, single attractor cellular automaton (SACA), synthesized in linear time O(n), generates a pattern and finally settles to a point state called the single length cycle attractor state. An analytical framework is developed around the graph-based tool referred to as the next state transition diagram to explore the properties of SACA rules for three-neighborhood, one-dimensional cellular automata. This enables synthesis of an (n+1)-cell SACA from the available configuration of an n-cell SACA in constant time and an (n+m)-cell SACA from the available configuration of n-cell and m-cell SACAs also in constant time.

Performance Analysis of Photovoltaic Systems Using (RAMD) Analysis

The primary aim of this present study is to examine how reliability, availability, maintainability, and dependability (RAMD) are used to describe the criticality of each sub-assembly in grid- connected photovoltaic systems. A transition diagram of all subsystems is produced for this analysis, and Chapman-Kolmogorov differential equations for each variable of each subsystem are constructed using the Markov birth-death process. Both random failure and repair time variables have an exponential distribution and are statistically independent. A sufficient repair facility is still available with the device. The numerical results for reliability, maintainability, dependability, and steady-state availability for various photovoltaic device components have been obtained. Other metrics, such as mean time to failure (MTTF), mean time to repair (MTTR), and dependability ratio, which aid in device performance prediction, have also been measured. According to numerical analysis. it is hypothesized that subsystem S4, i.e. the inverter, is the most critical and highly sensitive portion that requires special attention in order to improve the efficiency of the PV device plant. The findings of this research are very useful for photovoltaic system designers and maintenance engineers.

Application of Mobile Big Data and Artificial Intelligence in the Efficiency of E-Commerce Industry

In recent years, with the rapid development of network technology and mobile clients, the upsurge of online shopping users has been accelerated. The development of e-commerce has become a key factor affecting the economy. At the same time, in the process of online shopping, users produce a large number of user access data and transaction data, which seem messy but contain huge commercial value. E-commerce urgently needs to mine its own data information and related data so as to obtain competitive advantage. Web data mining technology has become the focus of research in universities and enterprises. This paper summarizes these two methods and explains their advantages and disadvantages, respectively. Next, based on the advantages and disadvantages of model control and logic analysis, a logic analysis method based on model control is proposed. A formal analysis method combining finite machine and logic is proposed. This new method can analyze the responsibility, fairness, and timeliness of e-commerce protocol, provide a state transition diagram describing the working principle of the protocol, and fully analyze the responsibilities of all parties when repeated attacks occur. Experiments show that the efficiency of e-commerce is improved by 30%. As mentioned above, this paper hopes to play a certain role in the development of e-commerce. This paper summarizes the time series of e-commerce data, sales changes, and the sensitivity of consumer goods, which is conducive to the prediction and evaluation of the market, seize the market trend, and provide better decision-making.

Analysis of the Current Situation of Piano Education in Colleges and Universities in the Information Age and Research on Countermeasures

In view of the low application ability of piano improvisational accompaniment of music majors, this paper proposes a method of big data combined with MIDI keyboard and Kinect depth sensor to achieve the purpose of recognizing chord progression and judging fingering when students perform, and realizes the auxiliary teaching system. Firstly, the information of color and depth images is obtained, and the state transition diagram of chord transposition and chord gesture template library are constructed as the system initialization conditions. Secondly, using the traditional skin color modeling and background difference method as well as the current depth data, the gesture recognition is realized by template matching. Finally, the correctness of chord progression is judged, and comprehensive fingering application is used to score and evaluate. The experimental results show that the system has high robustness and can be effectively applied to piano teaching.

Markov Modeling and Behavior Analysis of Steam Generation (SG) System in a Thermal Power Plant (TPP)

Steam generation (SG) system having five subsystems, namely Economizer, Reheater, Superheater, Furnace, Turbines, and Generator. The differential equations are acquired from the state transition diagram (STD) made pertaining to the real environment of the plant using Markov Method (MM). To get the performance of the system these equations are being worked out using normalizing conditions. The Performance values are attained by providing the apt values of failure and repair rates (FRRs) in the Markov model. Optimal Availability of the system is achieved with the Genetic algorithm (GA) technique.