Development of a novel ANFIS-GA method for investigation of effect of inhibitors on asphaltene precipitation

Asphaltene precipitation and deposition in different parts of petroleum industry increase considerably cost and problems in oil production. Due to these facts controlling asphaltene precipitation becomes one of valuable topics for research in petroleum engineering. Utilization of Asphaltene inhibitors is known as one of the dominant methods for controlling asphaltene precipitation so in this paper Adaptive neuro-fuzzy inference system (ANFIS) is joint with Genetic Algorithm (GA) to study effectiveness of asphaltene inhibitors on precipitation in terms of oil and inhibitors properties. In order to prepare and evaluate the ANFIS-GA algorithm, some reliable experimental data were gathered. The obtained results from the comparison shows the coefficient of determination (R²) for training and testing phases are 0.98804 and 0.9916 respectively. The determined indexes and graphical comparisons expresses that ANFIS-GA has enough accuracy and potential to estimate effectiveness of inhibitors on asphaltene precipitation reductions.     

An experimental study of the synergistic effects of BMIM.BF4, BMIM.DCA and TEACl aqueous solutions on methane hydrate formation

In this work, the effects of three ionic liquids (ILs), namely, 1-butyl-3-methylimidazolium tetrafluoroborate, 1-butyl-3-methylimidazolium dicyanamide and tetraethyl-ammonium chloride, on methane hydrate formation and dissociation kinetic parameters were studied. The kinetic parameters including the initial rate of hydrate formation, hydrate stability at atmospheric pressure and hydrate storage capacity were evaluated. The experimental measurements were performed in an initial pressure range of 3.5–7.1 MPa. It was found that both of ILs with imidazolium-based cation increase the initial methane hydrate formation rate while the IL with ammonium-based cation leads to a decrease in the initial methane hydrate formation rate. It was also interpreted from the results that all of the three studied ILs decrease methane hydrate stability at atmospheric pressure and increase methane hydrate storage capacity. Finally, both of ILs with imidazolium-based cations were found to have higher impacts on decreasing hydrate stability at atmospheric pressure and increasing the methane hydrate storage capacity than the applied IL with ammonium-based cation.     

Rakeness with block sparse Bayesian learning for efficient ZigBee‐based EEG telemonitoring

Future healthcare systems are shifted toward long‐term patient monitoring using embedded ultra‐low power devices. In this paper, the strengths of both rakeness‐based compressive sensing (CS) and block sparse Bayesian learning (BSBL) are exploited for efficient electroencephalogram (EEG) transmission/reception over wireless body area networks. A binary sensing matrix based on the rakeness concept is used to find the most energetic signal directions. A balance is achieved between collecting energy and enforcing restricted isometry property to capture the underlying signal structure. Correct presentation of the EEG oscillatory activity, EEG wave shape, and main signal characteristics is provided using the discrete cosine transform based BSBL, which models the intra‐block correlation. The IEEE 802.15.4 wireless communication technology (ZigBee) is employed, since it targets low data rate communications in an energy efficient manner. To alleviate noise and channel multipath effects, a recursive least square based equalizer is used, with an adaptation algorithm that continually updates the filter weights using successive input samples. For the same compression ratio (CR), results indicate that the proposed system permits a higher reconstruction quality compared with the standard CS algorithm. For higher CRs, lower dimensional projections are allowed, meanwhile guaranteeing a correct reconstruction. Thus, low computational high quality data compression/reconstruction are achieved with minimal energy expenditure at the sensors nodes.     

MC-CDMA with exponential power profile in Nakagami fading channel

A refined study of multi-carrier code division multiple access transmission over a Nakagami fading channel is proposed. The channel power is modeled with an exponential power profile rather than the uniform profile prevalent in other papers. An expression for the bit error rate (BER) is then derived. Numerical results show that MC-CDMA performances depend on the power dispersion of interferers around the desired user power.     

Potential Anomaly Separation and Archeological Site Localization Using Genetically Trained Multi‐level Cellular Neural Networks

In this paper, a supervised algorithm for the evaluation of geophysical sites using a multi‐level cellular neural network (ML‐CNN) is introduced, developed, and applied to real data. ML‐CNN is a stochastic image processing technique based on template optimization using neighborhood relationships of the pixels. The separation/enhancement and border detection performance of the proposed method is evaluated by various interesting real applications. A genetic algorithm is used in the optimization of CNN templates. The first application is concerned with the separation of potential field data of the Dumluca chromite region, which is one of the rich reserves of Turkey; in this context, the classical approach to the gravity anomaly separation method is one of the main problems in geophysics. The other application is the border detection of archeological ruins of the Hittite Empire in Turkey. The Hittite civilization sites located at the Sivas‐Altinyayla region of Turkey are among the most important archeological sites in history, one reason among others being that written documentation was first produced by this civilization.     

Collision Free Mobility Adaptive (CFMA) MAC for wireless sensor networks

In this paper we propose high throughput collision free, mobility adaptive and energy efficient medium access protocol (MAC) called Collision Free Mobility Adaptive (CFMA) for wireless sensor networks. CFMA ensures that transmissions incur no collisions, and allows nodes to undergo sleep mode whenever they are not transmitting or receiving. It uses delay allocation scheme based on traffic priority at each node and avoids allocating same backoff delay for more than one node unless they are in separate clusters. It also allows nodes to determine when they can switch to sleep mode during operation. CFMA for mobile nodes provides fast association between the mobile node and the cluster coordinator. The proposed MAC performs well in both static and mobile scenarios, which shows its significance over existing MAC protocols proposed for mobile applications. The performance of CFMA is evaluated through extensive simulation, analysis and comparison with other mobility aware MAC protocols. The results show that CFMA outperforms significantly the existing CSMA/CA, Sensor Mac (S-MAC), Mobile MAC (MOB-MAC), Adaptive Mobility MAC (AM-MAC), Mobility Sensor MAC (MS-MAC), Mobility aware Delay sensitive MAC (MD-MAC) and Dynamic Sensor MAC (DS-MAC) protocols including throughput, latency and energy consumption.     

SIW Corporate-Feed Network for Circular Polarization Slot Array Antenna

Wireless Personal Communications - In this paper, multilayer feeding network for linear slot array antenna is studied. A substrate integrated waveguide (SIW) corporate-feed network for linear slot...     

A partial-SOI LDMOSFET with triangular buried-oxide for breakdown voltage improvement

In this paper, a near-triangular buried-oxide partial silicon-on-insulator (TB-PSOI) lateral double-diffused MOS field-effect transistor is proposed. The electric field and electrostatic potential in this structure are modified by the gradual buried-oxide thickness increase. The modification includes the addition of a new peak in the electric field in comparison to that of the conventional PSOI. To assess the efficiency of the proposed structure, its breakdown voltage is compared with that of conventional PSOI using two-dimensional simulations. A comparative study is performed in terms of silicon-film and buried-oxide layer thicknesses, drift region and buried-oxide layer lengths, and drift region doping concentrations. The study shows that under the same drain current, the breakdown voltage of TB-PSOI is nearly two times higher than its PSOI counterpart (108% improvement). Simulation results show that the three-stepped oxide layer closely follows the TB-PSOI structure with a breakdown voltage improvement of 96% compared to that of the PSOI structure.     

Gain improvement and microwave operation of 4H–SiC MESFET with a new recessed metal ring structure

A new multi-recessed 4H-SiC MESFET with recessed metal ring for RF embedded circuits is proposed (MR2-MESFET). The key idea in the proposed structure is based on the elimination of the spaces adjacent to gate and stopped the depletion region extending towards drain and source and the reduction of the channel thickness between gate and drain to increase breakdown voltage (V_BR); meanwhile the elimination of the gate depletion layer extension to source/drain to decrease gate-source capacitance (C_gs). The influence of multi-recessed drift region and recessed metal ring structures on the characteristics of the MR2-MESFET is studied by numerical simulation. The optimized results show that the V_BR of the MR2-MESFET is 119% larger than that of the conventional 4H–SiC MESFET (C-MESFET); meanwhile maintain 85% higher saturation drain current. Therefore, the maximum output power density of the MR2-MESFET is 23.1 W/mm compared to 5.5 W/mm of the C-MESFET. Also, the cut-off frequency (f_T) and the maximum oscillation frequency (f_max) of 24.9 and 91.7 GHz are obtained for the MR2-MESFET compared to 11 and 40 GHz of the C-MESFET structure, respectively. The proposed MR2-MESFET shows a maximum stable gain (MSG) exceeding 23.6 dB at 3.1 GHz which is the highest gain yet reported for SiC MESFETs, showing the potential of this device for high power RF applications.     

Characterizing multi‐hop localization for Internet of things

Deployments over large geographical areas in the Internet of Things (IoT) pose a major challenge for single‐hop localization techniques, giving rise to applications of multi‐hop localizations. And while many proposals have been made on implementations for multi‐hop localization, a close understanding of its characteristics is yet to be established. Such an understanding is necessary, and is inevitable in extending the reliability of location based services in IoT. In this paper, we study the characteristics of multi‐hop localization and propose a new solution to enhance the performance of multi‐hop localization techniques. We first examine popular assumptions made in simulating multi‐hop localization techniques, and offer rectifications facilitating more realistic simulation models. We identify the introduced errors to follow the Gaussian distribution, and the estimated distance follows the Rayleigh distribution. We next use our simulation model to characterize the effect of the number of hops on localization in both dense and sparse deployments. We find that, contrary to common belief, it is better to use long hops in sparse deployments, while short hops are better in dense deployments – despite the traffic overhead. Finally, we propose a new solution that decreases and manages the overhead generated during the localization process. Copyright © 2016 John Wiley & Sons, Ltd.