SHSec: SDN based Secure Smart Home Network Architecture for Internet of Things

Mobile Networks and Applications - To address the challenges of flexible device utilization, heterogeneous device interoperability, and security enhancement in smart homes, this paper proposes a...     

Automatic Generation of Ortho-Photo Texture from Digital Elevation Model

We propose the automatic generation of the ortho-photo data which support realistic scenes for DEM by texture mapping. This ortho-photo data is automatically generated by pattern recognition techniques using Bayesian classifier which uses the features extracted from a DEM and its geo-referenced ortho-photo data as training sets. We defined the various features of each texel such as its height, slope angle, slope direction, surface curvature, hue, saturation and brightness from the training datasets. The proposed method makes possible for mapping texture of a realistic ortho-photo data to virtual terrain data which are unable to take satellite photo or aerial photo. These case are often in of computer game and digital movie area. Also, generating ortho-photo with the enlarged DEM, it does not cause the aliasing from the difference of resolution. It makes very similar images with real photography by shading and efficiently handles ortho-photo data and elevation data occupied enormous storage in cloud computing environment.     

Identification of important chemical features of 11β-hydroxysteroid dehydrogenase type1 inhibitors: application of ligand based virtual screening and density functional theory

11β-Hydroxysteroid dehydrogenase type1 (11βHSD1) regulates the conversion from inactive cortisone to active cortisol. Increased cortisol results in diabetes, hence quelling the activity of 11βHSD1 has been thought of as an effective approach for the treatment of diabetes. Quantitative hypotheses were developed and validated to identify the critical chemical features with reliable geometric constraints that contribute to the inhibition of 11βHSD1 function. The best hypothesis, Hypo1, which contains one-HBA; one-Hy-Ali, and two-RA features, was validated using Fischer's randomization method, a test and a decoy set. The well validated, Hypo1, was used as 3D query to perform a virtual screening of three different chemical databases. Compounds selected by Hypo1 in the virtual screening were filtered by applying Lipinski's rule of five, ADMET, and molecular docking. Finally, five hit compounds were selected as virtual novel hit molecules for 11βHSD1 based on their electronic properties calculated by Density functional theory.     

Adaptive network-based fuzzy inference model on CPS for large scale intelligent and cooperative surveillance

This paper proposes Cyber-Physical System (CPS) architectures for Large Scale Intelligent and Cooperative Surveillance (ICS) and presents an Adaptive Network-based Fuzzy Inference Model (ANFIM) for reducing the false accident-event report rates of Controller Manager (CM) systems among CPS components. In ICS, sensor nodes detect traffic accident events from general roads and crossroads and transmit event attribute values (car and accident types), time attribute values (date, month, day, year), environmental variable values (weather, temperature, luminous intensity, humidity and sound), and accident event videos to the Controller through WSN mesh networks. Using these pieces of information, the Controller conducts image processing and delivers all sensing data to the CM together with accident-event probability values. The CM conducts data filtering with multi regression analysis utilizing the past accident event database. Centering on the resultant values obtained through the foregoing process, this paper proposes a mathematical model for influence analysis of environmental variables that affect accident events. Based on the model’s results, the authors establish a Sugeno Type fuzzy rule base for reducing false accident-event report rates to propose an ANFIM.     

Synthesis of three-dimensional hierarchical BaCrO4 dendrites

3-D hierarchical superstructures of BaCrO₄ were prepared by a hydrothermal reaction of Ba(NO₃)₂ and Na₂CrO₄ in an aqueous-hexane bilayer system. A surfactant mixture of oleylamine and oleic acid was used to form hydrophobic barium oleate micelles. During the hydrothermal process, aqueous CrO₄^2? anions reacted at the interface with Ba²⁺ cations in the hexane phase to form BaCrO₄ crystals. 3-D hierarchical dendritic BaCrO₄ formed with a trunk and aligned, cruciform series of branches perpendicular to it. Scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM) confirmed that both trunk and branches preferentially grew in the < 001> direction. The dendrites formed through epitaxial growth.     

Short-term load forecasting for the holidays using fuzzy linear regression method

Average load forecasting errors for the holidays are much higher than those for weekdays. So far, many studies on the short-term load forecasting have been made to improve the prediction accuracy using various methods such as deterministic, stochastic, artificial neural net (ANN) and neural network-fuzzy methods. In order to reduce the load forecasting error of the 24 hourly loads for the holidays, the concept of fuzzy regression analysis is employed in the short-term load forecasting problem. According to the historical load data, the same type of holiday showed a similar trend of load profile as in previous years. The fuzzy linear regression model is made from the load data of the previous three years and the coefficients of the model are found by solving the mixed linear programming problem. The proposed algorithm shows good accuracy, and the average maximum percentage error is 3.57% in the load forecasting of the holidays for the years of 1996-1997.     

Lifetime maximization considering target coverage and connectivity in directional image/video sensor networks

A directional sensor network consists of a large number of directional sensors (e.g., image/video sensors), which have a limited angle of sensing range due to technical constraints or cost considerations. In such directional sensor networks, the power saving issue is a challenging problem. In this paper, we address the Directional Cover and Transmission (DCT) problem of organizing the directional sensors into a group of non-disjoint subsets to extend the network lifetime. One subset in which the directional sensors cover all the targets and forward the sensed data to the sink is activated at one time, while the others sleep to conserve their energy. For the DCT problem proven to be the NP-complete problem, we present a heuristic algorithm called the Shortest Path from Target to Sink (SPTS)-greedy algorithm. To verify and evaluate the proposed algorithm, we conduct extensive simulations and show that it can contribute to extending the network lifetime to a reasonable extent.     

Effect of precursor on epitaxially grown of ZnO thin film on p-GaN/sapphire (0 0 0 1) substrate by hydrothermal technique

Single crystalline ZnO thin film on p-GaN/sapphire (0 0 0 1) substrate, using two different precursors by hydrothermal route at a temperature of 90 °C were successfully grown. The effect of starting precursor on crystalline nature, surface morphology and optical emission of the films were studied. ZnO thin films were grown in aqueous solution of zinc acetate and zinc nitrate. X-ray diffraction analysis revealed that all the thin films were single crystalline in nature and exhibited wurtzite symmetry and c-axis orientation. The thin films obtained with zinc nitrate had a more pitted rough surface morphology compared to the film grown in zinc acetate. However the thickness of the films remained unaffected by the nature of the starting precursor. Sharp luminescence peaks were observed from the thin films almost at identical energies but deep level emission was slightly prominent for the thin film grown in zinc nitrate.     

Investigating Apache Hama: a bulk synchronous parallel computing framework

The quantity of digital data is growing exponentially, and the task to efficiently process such massive data is becoming increasingly challenging. Recently, academia and industry have recognized the limitations of the predominate Hadoop framework in several application domains, such as complex algorithmic computation, graph, and streaming data. Unfortunately, this widely known map-shuffle-reduce paradigm has become a bottleneck to address the challenges of big data trends. The demand for research and development of novel massive computing frameworks is increasing rapidly, and systematic illustration, analysis, and highlights of potential research areas are vital and very much in demand by the researchers in the field. Therefore, we explore one of the emerging and promising distributed computing frameworks, Apache Hama. This is a top level project under the Apache Software Foundation and a pure bulk synchronous parallel model for processing massive scientific computations, e.g. graph, matrix, and network algorithms. The objectives of this contribution are twofold. First, we outline the current state of the art, distinguish the challenges, and frame some research directions for researchers and application developers. Second, we present real-world use cases of Apache Hama to illustrate its potential specifically to the industrial community.     

Intra domain route optimization for ubiquitous network

The main advantage of a wireless network is user mobility, which calls for efficient routing support at the network layer. An architecture combines hierarchical mobile IPv6 and network mobility for a network mobile and mobile nodes move in tandem and make a hierarchy in the wireless network to management of micro-mobility and seamless handoff. But the capability of the architecture for intra domain route optimization is impaired. So we propose functionality in domain nodes to enable intra domain path optimization for ubiquitous network. It is shown that intra domain cost effect is beneficial in every hierarchical domain that spans mesh network topology. We address the key function for our proposed scheme and analyze the usefulness of our proposed method using mathematically. We show that our proposed scheme performs much better than Network Mobility protocol, especially when the number of mobile nodes or mobile routers or correspondent nodes increases in hierarchically nested in ubiquitous networks.