Learning Automata-Based Algorithms for Solving the Target Coverage Problem in Directional Sensor Networks

Recently, directional sensor networks have received a great deal of attention due to their wide range of applications in different fields. A unique characteristic of directional sensors is their limitation in both sensing angle and battery power, which highlights the significance of covering all the targets and, at the same time, extending the network lifetime. It is known as the target coverage problem that has been proved as an NP-complete problem. In this paper, we propose four learning automata-based algorithms to solve this problem. Additionally, several pruning rules are designed to improve the performance of these algorithms. To evaluate the performance of the proposed algorithms, several experiments were carried out. The theoretical maximum was used as a baseline to which the results of all the proposed algorithms are compared. The obtained results showed that the proposed algorithms could solve efficiently the target coverage problem.     

Introducing a dimensionless number as tank selector in hybrid solar thermal energy storage systems

Using hybrid energy storage system is a method for increasing the storage capability of solar thermal energy. If multiple energy storage devices with complementary performance characteristics are used together, the resulting system will be a ‘Hybrid Energy Storage System’. In other words, a Hybrid Energy Storage System (HESS) has several media available for storage at any time. In this way, increase in storable energy is obtained without increasing collectors’ area. When there are more than one storage mediums, the system should be able to choose the best medium for storing energy according to the conditions. In the previous works, an optimizer program was used to find the proper medium along time. But running a computer optimizer program is almost time consuming. So, in this work, a recognition parameter is introduced which helps to select the proper tank in different conditions. Using this dimensionless parameter, the hybrid storage system won’t be always dependent to the optimizer. The results have been checked theoretically and experimentally.     

Comparative Study of Conventional and Computerized Reconstruction Techniques for Flow Time Series Data of Hydrometric Station

Water Resources Management - One of the undeniable requirements in hydrological forecasting and water resources studies is the availability of reliable information. Due to the various reasons, time...     

Online preconcentration by transient isotachophoresis in linear polymer on a poly(methyl methacrylate) microchip for separation of human serum albumin immunoassay mixtures

Online preconcentration of human serum albumin (HSA) and its immunocomplex with a monoclonal antibody by on-chip transient isotachophoresis is reported. An 800-fold signal enhancement was achieved following the preconcentration on standard cross-channel microchips made of poly (methyl methacrylate). Sample injection, preconcentration, and separation were done continuously and controlled solely by a sequential voltage switching program. The preconcentration was followed by on-chip nondenaturing gel electrophoresis in methylcellulose solution. The method was applied to microchip electrophoresis immunoassay of HSA. Baseline separation of HSA and its immunocomplex was achieved in 25 s in the first 1 cm of the microchannel. In a direct immunoassay, the minimum detectable concentration of fluorescent labeled HSA by laser-induced fluorescence detection was 7.5 pM.     

Auto-Design of Neural Network–Based GAs for Manipulating the Khangiran Gas Refinery Sweetening Absorption Column Outputs

Abstract

In this work, a new approach for the auto-design of neural network-based genetic algorithm (GA) has been adopted to manipulate the products of an absorption column in the Khangiran gas refinery located in northeastern Iran. The experimental input data included gas flow rate, gas pressure, gas temperature, amine temperature, amine flow rate. In order to construct a GA–artificial neural network (ANN)-based model, the H₂S flow rate and dirty amine flow rate were selected for the output. The proposed method was assessed by the data taken from a case study in the Khangiran gas refinery. Design of topology and parameters of the neural networks as decision variables was first achieved by a trial-and-error procedure followed by genetic algorithms, which enhances the effectiveness of the forecasting scheme. The results reveal that the testing results from the model were in good agreement with the experimental data.     

Calculation of ρR-parameter and Energy Gain for Aneutronic Fusion in Degenerate P–11 B Plasma

Aneutronic fusion reactions are more safe and clean than the other reactions. One of the important candidate for these reactions is P–¹¹ B. This reaction in characteristic conditions creates degenerate plasma. In a Fermi-degenerate plasma, the electronic stopping of a slow ion is smaller than given by the classical formula, because some transitions between the electron states are forbidden. The bremsstrahlung losses are then smaller, so that the nuclear burning of an aneutronic fuel is more efficient. Practical obstacles in this regime that must be overcome before net energy can be realized include the compression of the fuel to an ultra dense state and the creation of a hot spot. In this paper, ρR parameter (Lawson’s criterion) and energy gain for P–¹¹ B are given.     

Application of High Energy Protons in Inertial Confinement Fusion by Using the Fast Ignitor Concept for DT Fusion

A short-laser-pulse driven ion flux is examined as a fast ignitor candidate for inertial confinement fusion. The main mechanism for ion acceleration is charge separation in a plasma due to high-energy electrons driven by the laser inside the target. Another very new branch of fast ignition research is the investigation of the use of laser generated proton beams. In the present paper aims to provide insights into the feasibility of the fast ignition concept with high energy beams of protons generated in laser–plasma interactions. The optimum parameters of an ion beam and laser pulse that are suitable for an ignition spark in a hot precompressed DT fuel are estimated as a rough guide. Also, in this paper we estimate the radius of Deuterium–Tritium (DT) fuel pellet that is equal to the protons range in DT plasma.     

Comparison of the classical and fracture mechanics approaches to determine in situ stress/hydrofracturing method

Bulletin of Engineering Geology and the Environment - The earth’s crustal stress determination is a crucial item in civil, petroleum, and mining engineering and also in energy development...     

Effects of solar transit in Ku-band VSAT systems

Behavior of networks of very small aperture satellite terminals (VSATs) operating at Ku band during the solar transit period, is compared to more traditional C or Ku-band satellite networks. Based on analyses and experiments, it is explained why solar transit outages are rarer in Ku-band VSAT systems than conventional satellite communications systems. In many cases, Ku-band VSAT systems will operate through periods of Sun transits without any significant increase in transmission error rates or incidences of link outages