Clustering of wireless sensor and actor networks based on sensor distribution and connectivity

Wireless Sensor and Actor Networks (WSANs) employ significantly more capable actor nodes that can collect data from sensors and perform application specific actions. To take these actions collaboratively at any spot in the monitored regions, maximal actor coverage along with inter-actor connectivity is desirable. In this paper, we propose a distributed actor positioning and clustering algorithm which employs actors as cluster-heads and places them in such a way that the coverage of actors is maximized and the data gathering and acting times are minimized. Such placement of actors is done by determining the k-hop Independent Dominating Set (IDS) of the underlying sensor network. Basically, before the actors are placed, the sensors pick the cluster-heads based on IDS. The actors are then placed at the locations of such cluster-heads. We further derive conditions to guarantee inter-actor connectivity after the clustering is performed. If inter-connectivity does not exist, the actors coordinate through the underlying sensors in their clusters to adjust their locations so that connectivity can be established. The performances of the proposed approaches are validated through simulations.     

Optimizing the hydrogen storage in boron nitride nanotubes by defect engineering

We use ab initio density functional theory calculations to study the interaction of hydrogen with vacancies in boron nitride nanotubes to optimize the hydrogen storage capacity through defect engineering. The vacancies reconstruct by forming B–B and N–N bonds across the defect site, which are not as favorable as heteronuclear B–N bonds. Our total energy and structure optimization results indicate that the hydrogen cleaves these reconstructing bonds to form more stable atomic structures. The hydrogenated defects offer smaller charge densities that allow hydrogen molecule to pass through the nanotube wall for storing hydrogen inside the nanotubes. Our optimum reaction pathway search revealed that hydrogen molecules could indeed go through a hydrogenated defect site with relatively small energy barriers compared to the pristine nanotube wall. The calculated activation energies for different diameters suggest a preferential diameter range for optimum hydrogen storage in defective boron nitride nanotubes.     

An Overview on Technologies for Access Nodes in Ultra-Fast OTDM Photonic Networks

In this paper, photonic technologies for the realization of high-capacity optical time-division multiplexed (OTDM) local and metropolitan area networks (LANs and MANs) are addressed including all-optical techniques such as ultra short pulse generation, all-optical clock recovery, optical multiplexing/demultiplexing, and optical packet compression/decompression. Furthermore, the new trends in high-speed electronics, data processing and optical interconnects are analyzed enabling the avoidance of the electronic processing bottleneck. By the use of both, high-speed electronics for implementing functions of higher complexity with higher level of parallelism and all-optical techniques for the realization of simple ultra fast (> 40 Gbit/s) medium access functions, a hybrid medium access node capable of handling high data rates can be designed.     

Electrical and photovoltaic properties of a n-Si/chitosan/Ag photodiode

The electrical and photovoltaic properties of AuSb/n-Si/chitosan/Ag diode have been investigated. The ideality factor, barrier height and Richardson constant values of the diode at room temperature were found to be 1.91, 0.88 eV and 121.4 A/cm² K², respectively. The ideality factor of the diode is higher than unity, suggesting that the diode shows a non-ideal behaviour due to series resistance and barrier height inhomogeneities. The barrier height and ideality factor values of Ag/CHT/n-Si diode at room temperature are significantly larger than that of the conventional Ag/n-Si Schottky diode. The φ_B value obtained from C-V measurement is higher than that of φ_B value obtained from I-V measurement. The discrepancy between φ_B(C-V) and φ_B(I-V) barrier height values can be explained by Schottky barrier height inhomogeneities. AuSb/n-Si/chitosan/Ag diode indicates a photovoltaic behaviour with open circuit voltage (V_oc = 0.23 V) and short-circuit current density (J_sc = 0.10 μA/cm⁻²) values.     

Research in moisture transport through one and two-layered porous composites

1 Introduction Moisture transport or general mass transport is a typical phenomenon that widely exists in porous ma- terials such as soil, construction or porous industrial materials. It is always accompanied with heat transfer and also a?ects temperature variation. A good under- standing of the mechanism of moisture transport pro- cesses is very important in various science areas such as soil science and agriculture, construction industry and chemical engineering[1]. For example, a success- f…     

The effect of nitrogen fertilization on tocopherols in rapeseed genotypes

Tocopherols (α-, β-, γ- and δ-tocopherol) are naturally occuring antioxidants in vegetable oils. In rapeseed oil, α- and γ-tocopherols are the predominant isomers, while δ-tocopherol contributes much lower amounts to the total tocopherol content. Enhanced tocopherol content in seeds appears favourable, and breeding for tocopherol content has become an increasingly important objective in winter oilseed rape. The main objectives of this research were to quantify the amount of tocopherols in a number of rapeseed varieties and to investigate the effect of nitrogen fertilization on tocopherol concentration in the seed. The field trials were carried out in 2004–2005 and 2005–2006 at Dardanos, Çanakkale on the Turkish West Coast (10 km south of the city centre) with 13 varieties, three replications and three nitrogen levels (N₀: 0 kg/ha, N₁: 130 kg/ha and N₂: 260 kg/ha). The trial used a randomized complete block design with 6 m² plots. Tocopherol analysis was done using an HPLC system. Significant differences were found among the varieties and between the nitrogen levels. The average total tocopherol concentration was 118.7 mg kg^?1 for N₁, 134.1 mg kg^?1 for N₂ and 133.6 mg kg^?1 for N₃ fertilization level. MDS analysis indicated a rough grouping of line versus hybrid varieties and suggested that hybrids require more breeding effort to reach the level of tocopherols existed in line varieties.     

Elastic,electronic, and vibrational properties of RhN compound

The structural, electronic, mechanical, and vibrational properties of 4d transition metal mononitride, RhN, are investigated using the norm-conserving pseudopotentials within the local density approximation (LDA) in the frame of density functional theory. The calculated lattice parameters and the bulk modulus almost agree with the previous theoretical values. The second-order elastic constants have been calculated and the other related quantities such as Young’s modulus, shear modulus, anisotropy factor, sound velocities, and Debye temperature also estimated. Charge distributions and density of states are reported to understand the bonding character in the stable phases. We have also obtained the phonon dispersion curves without LO/TO splitting.     

Effect of low copper content and heat treatment on intergranular corrosion of model AlMgSi alloys

Certain 6000-series extrusions may develop susceptibility to intergranular corrosion (IGC) by improper heat treatment, especially if copper is present as an alloying element. Although occurrence of IGC in such cases is documented, the underlying mechanisms are not adequately explained. We present corrosion data for two model alloys, having different Cu content and Mg:Si ratio, showing that the susceptibility to IGC depended primarily on the Cu content and secondly on thermal processing. Low Cu samples (0.0005 wt.% Cu) were essentially resistant to IGC. High Cu samples (0.12 wt.% Cu), which were air cooled after extrusion, exhibited significant IGC. However, IGC susceptibility was reduced significantly as a result of artificial aging to peak strength. Water quenched high Cu samples were essentially resistant to IGC. However, slight IGC susceptibility was introduced after aging. Electron optical characterisation revealed Al₄Mg₈Si₇Cu₂ (Q-phase) grain boundary precipitates on all the variants susceptible to IGC. The susceptibility was attributed to microgalvanic coupling between Q-phase grain boundary precipitates (noble) and the adjacent depleted zone (active).     

Topological properties of the crossed cube architecture

Crossed cube is a variant obtained from the hypercube by redirecting a subset of the edges to span two or more dimensions. As a result, the diameter is reduced by half without increasing the link complexity. The use of the crossed cube as a parallel architecture, and in a reconfigurable system has been investigated earlier. The topological properties of the crossed cube are investigated in this paper. The main results of this paper include: an analysis of the number of isomorphic subgraphs, a formal proof for the diameter, and some new embedding properties.     

A hybrid medical decision making system based on principles component analysis, k-NN based weighted pre-processing and adaptive neuro-fuzzy inference system

Proper interpretation of the thyroid gland functional data is an important issue in diagnosis of thyroid disease. The primary role of the thyroid gland is to help regulation of the body's metabolism. Thyroid hormone produced by thyroid gland provides this. Production of too little thyroid hormone (hypo-thyroidism) or production of too much thyroid hormone (hyper-thyroidism) defines the types of thyroid disease. It is evident that usage of machine learning methods in disease diagnosis has been increasing gradually. In this study, diagnosis of thyroid disease, which is a very common and important disease, was conducted with such a machine learning system. In this study, we have detected on thyroid disease using principles component analysis (PCA), k-nearest neighbor (k-NN) based weighted pre-processing and adaptive neuro-fuzzy inference system (ANFIS). The proposed system has three stages. In the first stage, dimension of thyroid disease dataset that has 5 features is reduced to 2 features using principles component analysis. In the second stage, a new weighting scheme based on k-nearest neighbor (k-NN) method was utilized as a pre-processing step before the main classifier. Then, in the third stage, we have used adaptive neuro-fuzzy inference system to diagnosis of thyroid disease. We took the thyroid disease dataset used in our study from the UCI machine learning database. The obtained classification accuracy of our system was 100% and it was very promising with regard to the other classification applications in literature for this problem.