ADAPTIVE COORDINATION OF DISTANCE PROTECTION ON SUBTRANSMISSION LINES CONSIDERING THE INFEED EFFECT

ABSTRACT: This article describes an algorithm for an adaptive distance protection in a sub-transmission system considering operating conditions with changes in the topology due to an abnormal condition, electrical failure or a natural disaster, includes the effect of adjacent generation in the distance relay protection zones, with the incorporation of renewable energies in mixed participation. Two scenarios are proposed, in the first case occurred a contingency, and the transmission systems changes the initial topology. Protections are automatically reparametrized. The second case includes the income of renewable energy generation in a specific point of power electrical Systems. Protections are automatically recalculated. The objective of an automatic coordination permit to operator to restore the sensitivity, selectivity and reliability the electrical protection system in the lowest time. Keywords: Adaptive distance relay, renewable energy, distance protection, infeed effect..)

Adaptive Deep Rider LSTM-enabled Objective Functions for RPL routing in IoT applications

This paper presents a proposed Objective Function (OF) design using various routing metrics for improving the performance of IoT applications. The most important idea of the proposed design is the selection of the routing metrics with respect to the application requirements. The various metrics, such as Energy, Distance, Delay, Link quality, Trust (EDDLT) are used for improving the objective function design of the RPL in various IoT applications. Here, the Adaptive Deep rider LSTM is newly employed for the energy prediction where the Adaptive Deep Rider LSTM is devised by the combination of the adaptive theory with the Rider Adam Algorithm (RAA), and the Deep-Long Short Memory (Deep-LSTM). However, the evaluation of the proposed method is carried out energy dissipation, throughput, and delay by achieving a minimum energy dissipation of 0.549, maximum throughput of 1, and a minimum delay of 0.191, respectively.

Combination of improved Harris’s hawk optimization with fuzzy to improve clustering in wireless sensor network

A Wireless Sensor Network (WSN) is divided into groups of sensor nodes for efficient transmission of data from the point of measuring to sink. By performing clustering, the network remains energy-efficient and stable. An intelligent mechanism is needed to cluster the sensors and find an organizer node, the cluster head. The organizer node assembles data from its constituent nodes called member nodes, finds an optimal route to the sink of the network, and transfers the same. The nomination of cluster head is crucial since energy utilization is a major challenge of sensor nodes deployed over a hostile environment. In this paper, a fuzzy-based Improved Harris’s Hawk Optimization Algorithm (IHHO) is proposed to select an able cluster head for data communication. The fuzzy inference model ponders balance energy, distance from self to sink node, and vicinity of nodes from cluster head as input factors and decides if a candidate node is eligible for becoming a cluster head. The IHHO tunes the logic into an energy-efficient network with less complexity and more ease. The novelty of the paper lies in applying the hawk-pack technique based on fuzzy rules. Simulations show that the combination of Fuzzy based IHHO reduces the death of nodes through which network lifetime is enhanced.

TIMED SIGNAL CONSTRUCTIONS AS A TOOL FOR INCREASING THE NUMBER OF CODEWORDS BY IMPLEMENTING THEIR CONSTANT LENGTH

It is indicated that due to changes in the restrictions on the duration of the basic element, which is the basis for the construction of the signal structure, an increase in the channel capacity was obtained by reducing the energy distance between the signal structures. In this case, the information parameter in these structures is not the parameters of the current or voltage, but the time. The work uses timer signal structures, which are synthesized, as well as positional signals from segments not less than the Nyquist element, but not multiples of it. It is this principle of formation that significantly increases the number of synthesized code structures in comparison with positional coding. It is noted that the information content of any event is determined by the number of its states, and the entropy and the probability of the occurrence of a particular event are interrelated values. In addition, timer signaling constructs allow synthesizing ensembles with a large information content in comparison with positional coding. Keywords: basic element, Nyquist element, information parameter, entropy, probability of occurrence, information segment, message, timer signal structure.

Mechanisms for the creation of intrinsic electron-hole trapping centers in a CaSO4 crystall

The mechanism of creation of electron-hole trapping centers in CaSO4 at 15-300 K was investigated by the methods of vacuum-ultraviolet and thermoactivation spectroscopy. It is shown that electron-hole trapping centers are formed upon trap of electrons in the anionic complexes SO4− and localization of holes in the form of SO4− radical. Based on the measurement of the spectrum of excitation of long-wavelength recombination emission at 3.0-3.1 eV and 2.7 eV, the energy distance of the formed electron-hole trapping centers was estimated (4.43 eV and 3.87 eV).

Quantifying the Differences Between Lexical Categories

The Cambridge grammar of the English language (HUDDLESTON; PULLUM, 2002) attempts to present a comprehensive and rigorous description of Modern Standard English. Much of the book is taken up with describing the properties of the various lexical categories, including determinative and pronoun. The distinction between these categories has been questioned by various authors in English (ABNEY, 1987; CROFT, 2001; HUDSON, 2004; MATTHEWS, 2014; POSTAL, 2014/1966; SOMMERSTEIN, 1972) and other languages (e.g., NAU, 2016). Here, I employ energy distance, a novel family of non-parametric statistics, to adjudicate between these positions. Following Crystal (1967), I binarily encode the features (has/doesn’t have feature) of the determinatives and pronouns from CGEL in a 138 word-forms by 232 features matrix. The results provide support for CGEL’s analysis (k-groups produces a 93% correspondence with CGEL’s categorization) and show that energy distance statistics applied to such matrices can help us adjudicate between competing lexical category analyses without resorting to methodological opportunism (CROFT, 2001).

Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks

Localization is recognized among the topmost vital features in numerous wireless sensor network (WSN) applications. This paper puts forward energy-efficient clustering and localization centered on genetic algorithm (ECGAL), in which the residual energy, distance estimation, and coverage connection are developed to form the fitness function. This function is certainly fast to run. The proposed ECGAL exhausts a lesser amount of energy and extends wireless network existence. Finally, the simulations are carried out to assess the performance of the proposed algorithm. Experimental results show that the proposed algorithm approximates the unknown node location and provides minimum localization error.

Advanced Energy Efficient Master/Slave Algorithm in Wireless Sensor Networks

The nodes in WSNs are densely deployed and lots of redundancy exists during the data gathering and sending perceived data straightforwardly to the base station, which leading to consumption of energy in nodes. Existing Clustering algorithms in WSN selects just one group head in the each cluster, where it devours more energy at Cluster head(CH) quickly and which condenses lifetime of the network incredibly. The paper proposes the Advanced and Energy Efficient Master/Slave algorithm to solve this problem. The algorithm reduces the energy consumption of each node by minimizing the direct communication of the nodes with the Base station or CHs by changing the hierarchy in WSN. The moto of the algorithm is to select one master Cluster Head and remaining slave CHs. The algorithm will select Master Cluster Head based on more residual energy, distance, and low packet drop; the remaining become Slave Cluster Heads. The simulation results prove that the Advanced and Energy Efficient Master/Slave algorithm improves throughput and packet delivery ratio(PDR) by decreasing the energy consumption.

Selective Extraction of Piceatannol from Passiflora edulis By-Products: Application of HSPs Strategy and Inhibition of Neurodegenerative Enzymes

Passiflora edulis by-products (PFBP) are a rich source of polyphenols, of which piceatannol has gained special attention recently. However, there are few studies involving environmentally safe methods for obtaining extracts rich in piceatannol. This work aimed to concentrate piceatannol from defatted PFBP (d-PFBP) by means of pressurized liquid extraction (PLE) and conventional extraction, using the bio-based solvents selected with the Hansen solubility parameters approach. The relative energy distance (Ra) between solvent and solute was: Benzyl Alcohol (BnOH) < Ethyl Acetate (EtOAc) < Ethanol (EtOH) < EtOH:H2O. Nonetheless, EtOH presented the best selectivity for piceatannol. Multi-cycle PLE at 110 °C was able to concentrate piceatannol 2.4 times more than conventional extraction. PLE exhibited a dependence on kinetic parameters and temperature, which could be associated with hydrogen bonding forces and the dielectric constant of the solvents. The acetylcholinesterase (AChE) and lipoxygenase (LOX) IC50 were 29.420 μg/mL and 27.682 μg/mL, respectively. The results reinforce the demand for processes to concentrate natural extracts from food by-products.