The Eastern Academy of Science and Technology, Bhubaneswar, (or EAST) is a private technical institution situated in Orissa, India. The college is located on the banks of the dried river Prachi at Phulnakhra in Bhubaneswar. The institute offers diploma, bachelor and masters technical courses.
Automatic generation control is extensively used to regulate power plants in a modern area of the power system network. In this paper, automatic generation and frequency control in interconnected power system is presented. A multisource such as thermal, hydro, and gas-based power plant is considered in this study, which is carried out by incorporating nonlinearity like generation rate constants, HVDC link, and the conventional PID controller design. Further, an optimal setting of the PID controller is performed by employing evolutionary, and metaheuristic algorithm-based approaches such as differential evolution and firefly algorithm, respectively. With these algorithms, the proposed model has been tested with their performance evaluation and comparison characteristics are discoursed. The robustness of the proposed controllers is assessed based on comparative analyses to regulate the interconnected power network's frequency profile under different loading conditions. The stability analysis is performed using the Eigen and Nyquist plots to assess the proposed controllers' efficacy. Besides, the frequency control study is summarized with comparative assessment through various performance indices such as settling time, peak overshoot and undershoots under different operating conditions. Finally, the proposed control scheme, in the interconnected power system, is validated through a real-time digital simulation platform, i.e., OPAL-RT 5142. The comparison of simulation and real-time results demonstrates the effectiveness of the FA-optimized PID controller in comparison with that of the DE-optimized PID controller.
Wireless Sensor Network(WSN) is an integral part of Internet of Things (IoT) application network. Cost-effective WSN routing will help IoT applications to offer faster services in an efficient way. Routing in WSN is one of the challenging task due to node mobility and need on small battery to ruins active in the network. Flat routing shows poor performance for WSN if number of node increase. Cluster based routing is the alternative that is scalable and shows better utilization of network resources. The data transmission cost will be more,if the sender nodes send data directly to sink node due to large distance of data transmission and the node battery power dry very soon. To overcome this problem data packets send from sender node to sink node via cluster head node. The member nodes of a cluster send data packets to its header node,then the header node send the data packets to sink node. In our proposed method, the fuzzy inference system uses three Quality of Service (QoS) parameters distance, energy and angle to select the chance of a node becomes cluster head. Iterative Deepening A*(IDA*) search used to discover the shortest route that send data packets from supply node to the sink node. The fuzzy system is used to select the cluster head and IDA* search algorithm used to select the minimal cost path. The proposed method - Cost Effective Routing in WSN Using Fuzzy IDA*(CERWFI) is used to find an optimal route from starting node to ending node (sink). The research concludes by stating that space complexity of Dijkstra's and A* algorithm can be improved by IDA* algorithm.
Background: Surfactant adsorption at the interfaces (solid–liquid, liquid–air, or liquid–liquid) is receiving considerable attention from a long time due to its wide range of practical applications. Objective: Specifically wettability of solid surface by liquids is mainly measured by contact angle and has many practical importances where solid–liquid systems are used. Adsorption of surfactants plays an important role in the wetting process. The wetting behaviours of three plant-based natural surfactants (Reetha, Shikakai, and Acacia) on the glass surface are compared with one widely used nonionic synthetic surfactant (Triton X-100) and reported in this study. Methods: The dynamic contact angle study of three different types of plant surfactants (Reetha, Shikakai and Acacia) and one synthetic surfactant (Triton X 100) on the glass surface has been carried out. The effect of two different types of alcohols such as Methanol and amyl alcohol on wettability of shikakai, as it shows little higher value of contact angle on glass surface has been measured. Results: The contact angle measurements show that there is an increase in contact angle from 47° (pure water) to 67.72°, 65.57°, 68.84°, and 68.79° for Reetha, Acacia, Shikakai, and Triton X-100 respectively with the increase in surfactant concentration and remain constant at CMC. The change in contact angle of Shikakai-Amyl alcohol mixtures are slightly different than that of methanol-Shikakai mixture, mostly there is a gradual increase in contact angle with the increasing in alcohol concentration. Conclusion: There is no linear relationship between cos θ and inverse of surface tension. There was a linear increase in surface free energy results with increase in concentration as more surfactant molecules were adsorbing at the interface enhancing an increase in contact angle.
In this paper a trigonometric functional link artificial neural network (FLANN) model using backpropagation rule is applied to predict the next day's spot price of US crude oil. The daily observations of these variables: US dollar index, S&P 500 stock price index, gold spot price, heating oil spot price and US crude oil spot price are employed as inputs of the proposed model. By comparing with multilayer backpropagation feedforward neural network (FNN), more accurate predictions were shown by applying the FLANN model. In fact, several performance criteria are used to assess the forecasting power of the proposed model such as the Root Mean Squared Error (RMSE), the Mean Absolute Error (MAE) and the hit rate. For checking the forecasting robustness of the proposed model, in addition to the other input variables, the US crude oil and biofuels production are also used to predict the next month's spot price of crude oil. Comparatively, similar conclusion was deduced and the FLANN model performs better than the standard FNN. These findings can be explained by the simplicity of FLANN structure since it consists of a single layer with only one neuron at the output thus a lower computational load on the network.
In recent trends, wireless networks have emerged as one of the choicest forms of data communication. Wireless networks provide an array of benefits like, easy installation, flexibility, mobility, scalability and reduced cost of ownership. In spite of several advantages, there are some serious issues, which pose security risks when confidentiality, integrity and authenticity issues are concerned. In infrastructure wireless networks, providing access only to legitimate users is a challenge to most network administrators. Attackers are equipped with various tools and techniques to break the security and gain illegitimate access to the organization's data and other such secured entities. Some of the wireless networks employ MAC filtering techniques for providing network access to hosts. In order to gain unauthorized access to such networks spoofing- attack with false IP-MAC pair is the first step in most of the LAN based attacks. Address Resolution Protocol (ARP) is the main cause of spoofing attack. Many network and host level mechanisms have been proposed to counter such attacks. However, they have their own sets of drawbacks. In our proposed work, we have configured an open source network security tool for the detection of various attacks or spoofed MAC attack exploited in IEEE 802.11 wireless networks. In this work, we have tried to differentiate between the genuine station and the attacker station by 3-phase authentication method. In our proposed work the algorithms are developed upon three phase i.e. probe request frame, authentication frame and association frame. This scheme has been tested under all possible spoofing cases and yielded favorable results.
