Low-Complexity Detection/Equalization in Large-Dimension MIMO-ISI Channels Using Graphical Models

In this paper, we deal with low-complexity near-optimal detection/equalization in large-dimension multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels using message passing on graphical models. A key contribution in the paper is the demonstration that near-optimal performance in MIMO-ISI channels with large dimensions can be achieved at low complexities through simple yet effective simplifications/approximations, although the graphical models that represent MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1) use of Markov Random Field (MRF) based graphical model with pairwise interaction, in conjunction with {\em message/belief damping}, and 2) use of Factor Graph (FG) based graphical model with {\em Gaussian approximation of interference} (GAI). The per-symbol complexities are $O(K^2n_t^2)$ and $O(Kn_t)$ for the MRF and the FG with GAI approaches, respectively, where $K$ and $n_t$ denote the number of channel uses per frame, and number of transmit antennas, respectively. These low-complexities are quite attractive for large dimensions, i.e., for large $Kn_t$. From a performance perspective, these algorithms are even more interesting in large-dimensions since they achieve increasingly closer to optimum detection performance for increasing $Kn_t$. Also, we show that these message passing algorithms can be used in an iterative manner with local neighborhood search algorithms to improve the reliability/performance of $M$-QAM symbol detection

Establishing Self-Healing and Seamless Connectivity among IoT Networks Using Kalman Filter

The Internet of Things (IoT) is the extension of Internet connectivity into physical devices and to everyday objects. Efficient mobility support in IoT provides seamless connectivity to mobile nodes having restrained resources in terms of energy, memory and link capacity. Existing routing algorithms have less reactivity to mobility. So, in this work, a new proactive mobility support algorithm based on the Kalman Filter has been proposed. Mobile nodes are provided with a seamless connectivity by minimizing the switching numbers between point of attachment which helps in reducing signaling overhead and power consumption. The handoff trigger scheme which makes use of mobility information in order to predict handoff event occurrence is used.  Mobile nodes new attachment points and its trajectory is predicted using the Kalman-Filter. Kalman-Filter is a predictor-estimator method used for movement prediction is used in this approach. Kalman Filtering is carried out in two steps: i) Predicting and ii) Updating. Each step is investigated and coded as a function with matrix input and output. Self-healing characteristics is being considered in the proposed algorithm to prevent the network from failing and to help in efficient routing of data. Proposed approach achieves high efficiency in terms of movement prediction, energy efficiency, handoff delay and fault tolerance when compared to existing approach

Implicit self-consistent electrolyte model in plane-wave density-functional theory

The ab-initio computational treatment of electrochemical systems requires an appropriate treatment of the solid/liquid interfaces. A fully quantum mechanical treatment of the interface is computationally demanding due to the large number of degrees of freedom involved. In this work, we describe a computationally efficient model where the electrode part of the interface is described at the density-functional theory (DFT) level, and the electrolyte part is represented through an implicit solvation model based on the Poisson-Boltzmann equation. We describe the implementation of the linearized Poisson-Boltzmann equation into the Vienna Ab-initio Simulation Package (VASP), a widely used DFT code, followed by validation and benchmarking of the method. To demonstrate the utility of the implicit electrolyte model, we apply it to study the surface energy of Cu crystal facets in an aqueous electrolyte as a function of applied electric potential. We show that the applied potential enables the control of the shape of nanocrystals from an octahedral to a truncated octahedral morphology with increasing potential

Effect of low-level jet height on wind farm performance

Low-level jets (LLJs) are the wind maxima in the lowest 50 to 1000 m of atmospheric boundary layers. Due to their significant influence on the power production of wind farms it is crucial to understand the interaction between LLJs and wind farms. In the presence of an LLJ, there are positive and negative shear regions in the velocity profile. The positive shear regions of LLJs are continuously turbulent, while the negative shear regions have limited turbulence. We present large-eddy simulations of wind farms in which the LLJ is above, below, or in the middle of the turbine rotor swept area. We find that the wakes recover relatively fast when the LLJ is above the turbines. This is due to the high turbulence below the LLJ and the downward vertical entrainment created by the momentum deficit due to the wind farm power production. This harvests the jet's energy and aids wake recovery. However, when the LLJ is below the turbine rotor swept area, the wake recovery is very slow due to the low atmospheric turbulence above the LLJ. The energy budget analysis reveals that the entrainment fluxes are maximum and minimum when the LLJ is above and in the middle of the turbine rotor swept area, respectively. Surprisingly, we find that the negative shear creates a significant entrainment flux upward when the LLJ is below the turbine rotor swept area. This facilitates energy extraction from the jet, which is beneficial for the performance of downwind turbines

Lightweight Encrytion Scheme against Flow Analysis in Multi-Hop Wireless Network Based on Network Coding

Traffic analysis is a major issue faced in multi-hop wireless networks (MWN) in the case of privacy preservation. Network coding is essential in achieving greater capacity for any network and we extend this network coding for privacy preservation in multi-hop networks as it offers coding and mixing functions at intermediate nodes. Certain existing privacy preserving methods like onion routing can be employed here. Applying homomorphic encryption on Global Encoding Vectors(GEV’s), our method offers confidentiality and privacy preserving features. Only the sink has capability of decrypting the message content by inverting the GEV. Here, we focus on the privacy issue in order to prevent traffic analysis and flow tracing and achieve source anonymity in MWNs. Source anonymity refers to carrying the communication through the network maintaining the secrecy of the source node. Energy consumption when compared with the existing system was found to be reduced. Simulative evaluation by NS2 shows the efficiency of the system. Keywords: MWN, Privacy preservation, NS2, GEV

The Mean Wind and Potential Temperature Flux Profiles in Convective Boundary Layers

We develop innovative analytical expressions for the mean wind and potential temperature flux profiles in convective boundary layers (CBLs). CBLs are frequently observed during daytime as the Earth's surface is warmed by solar radiation. Therefore, their modeling is relevant for weather forecasting, climate modeling, and wind energy applications. For CBLs in the convective-roll dominated regime, the mean velocity and potential temperature in the bulk region of the mixed layer are approximately uniform. We propose an analytical expression for the normalized potential temperature flux profile as a function of height, using a perturbation method approach in which we employ the horizontally homogeneous and quasi-stationary characteristics of the surface and inversion layers. The velocity profile in the mixed layer and the entrainment zone is constructed based on insights obtained from the proposed potential temperature flux profile and the convective logarithmic friction law. Combining this with the well-known Monin-Obukhov similarity theory allows us to capture the velocity profile over the entire boundary layer height. The proposed profiles agree excellently with large-eddy simulation results over the range of $-L/z_0 \in [3.6\times10^2, 0.7 \times 10^5]$, where $L$ is the Obukhov length and $z_0$ is the roughness length.Comment: 12 pages, 6 figure

Universal Wind Profile for Conventionally Neutral Atmospheric Boundary Layers

Conventionally neutral atmospheric boundary layers (CNBLs), which are characterized with zero surface potential temperature flux and capped by an inversion of potential temperature, are frequently encountered in nature. Therefore, predicting the wind speed profiles of CNBLs is relevant for weather forecasting, climate modeling, and wind energy applications. However, previous attempts to predict the velocity profiles in CNBLs have had limited success due to the complicated interplay between buoyancy, shear, and Coriolis effects. Here, we utilize ideas from the classical Monin-Obukhov similarity theory in combination with a local scaling hypothesis to derive an analytic expression for the stability correction function $\psi = -c_\psi (z/L)^{1/2}$, where $c_\psi = 4.2$ is an empirical constant, $z$ is the height above ground, and $L$ is the local Obukhov length based on potential temperature flux at that height, for CNBLs. An analytic expression for this flux is also derived using dimensional analysis and a perturbation method approach. We find that the derived profile agrees excellently with the velocity profile in the entire boundary layer obtained from high-fidelity large eddy simulations of typical CNBLs.Comment: 11 pages, 6 figures, the article has been accepted by Physical Review Letters, see https://journals.aps.org/prl/accepted/2807bYecI411db78409a3879761405c3a75de2a0

Demarcation of Ground Water Potential Zones using Remote Sensing and GIS Applications

Now-a-days, due to the high demand of water for the human needs, groundwater sources are drastically extracted and causing to least the source. The entire Yearly furnish is contributing from the utmost resource called Groundwater. Globally, groundwater is extracting primarily for the purpose of agricultural fields, domestic and for industrial water supply. Majority of the surface water is in the form of saline water which is not useful for the needs of human beings for their daily needs. Very less amount of fresh surface water is existing on the ground surface. To compensate the needs, it is essential to identify, extract and manage the groundwater which is available at different levels at different areas of the globe. Proper planning is required for the extraction of groundwater using updated technologies for using and maintaining of natural resources like water resources. The prime strive of the selected project area is to map out potential groundwater regions in the Pendlimarri Mandal of Kadapa District by using Geospatial Technology. The main impartial target of the work is to select appropriate methods and assessment criteria of the technology to identify the potential underground demarcations in geographic information system environment with help of ArcGIS software. To demarcate zones of groundwater potential, various key parameters called geology, lineament density, LU / LC, geomorphology, groundwater depths, slope and drainage pattern were prepared by utilizing remote sensing data and secondary data which can collect from concern departments. The thematic layers are to be finally integrated by using weighted overlay analysis of spatial analyst tools of data management tools of ArcMap software to delineate underground water prospects regions output layout of the project. Disparate groundwater prospects levels were categorized, from the range excellent to poor including very good, good and moderate in between. At last, decided that that the applications of geoinformatics are essential and effectively applied for the demarcation of potential zones of groundwater

Association of FADS2 rs174575 gene polymorphism and insulin resistance in type 2 diabetes mellitus

Background: Many risk factors contribute to the pathogenesis of diabetes. Gene and lifestyle factors are considered to be the major contributors. A dietary pattern is attributed to be one of the lifestyle risk factors favoring diabetes. The present study aims to find an association between fatty acid desaturase (FADS) gene polymorphism and glycemic profile in type 2 diabetes mellitus (T2DM). Methodology: A total of 429 subjects were included in the study on the basis of inclusion and exclusion criteria, of which 213 and 216 subjects were diabetic and control, respectively. Body mass index was calculated. Fasting plasma glucose, glycated hemoglobin (HbA1c) and insulin were measured using commercially available kits. rs174575 of FADS2 was selected based on previous publications and identified using the dbSNP database. To compare the biochemical parameters with the genotype, the following three models were used: additive model (CC vs CG vs GG), dominant model (CC + CG vs GG), and recessive model (CC vs CG + GG). Results and Discussion: FBS, HbA1c, insulin, HOMA-IR, and HOMA-B exhibited a high and statistically significant difference between subjects and controls. The three models exhibited a statistically significant difference between FBS, HOMA-IR, and HOMA- B (p<0.05). Conclusion: The distribution of rs174575 genotype differed significantly between the subjects and controls in the present study. The study revealed that genetic variation in FADS2 is an additional facet to consider while studying the risk factors of T2DM