Deposition and characterization of molybdenum thin films using dc-plasma magnetron sputtering

Molebdenum (Mo) thin films were deposited on well-cleaned soda-lime glass substrates using DC-plasma magnetron sputtering. In the design of experiment deposition was optimized for maximum beneficial characteristics by monitoring effect of process variables such as deposition power (100–200 W). Their electrical, structural and morphological properties were analyzed to study the effect of these variables. The electrical resistivity of Mo thin films could be reduced by increasing deposition power. Within the range of analyzed deposition power, Mo thin films showed a mono crystalline nature and the crystallites were found to have an orientation along [110] direction. The surface morphology of thin films showed that a highly dense micro structure has been obtained. The surface roughness of films increased with deposition power. The adhesion of Mo thin films could be improved by increasing the deposition power. Atomic force microscopy was used for the topographical study of the films and to determine the roughness of the films. X-ray diffractrometer and scanning electron microscopy analysis were used to investigate the crystallinity and surface morphology of the films. Hall effect measurement system was used to find resistivity, carrier mobility and carrier density of deposited films. The adhesion test was performed using scotch hatch tape adhesion test. Mo thin films prepared at deposition power of 200 W, substrate temperature of 23°C and Ar pressure of 0.0123 mbar exhibited a mono crystalline structure with an orientation along (110) direction, thickness of ～550 nm and electrical resistivity value of 0.57 × 10^?4 Ω cm.     

The convex hull property and topology of hypersurfaces with nonnegative curvature

We prove that, in Euclidean space, any nonnegatively curved, compact, smoothly immersed hypersurface lies outside the convex hull of its boundary, provided the boundary satisfies certain required conditions. This gives a convex hull property, dual to the classical one for surfaces with nonpositive curvature. A version of this result in the nonsmooth category is obtained as well. We show that our boundary conditions determine the topology of the surface up to at most two choices. The proof is based on uniform estimates for radii of convexity of these surfaces under a clipping procedure, a noncollapsing convergence theorem, and a gluing procedure.     

Achieving Outstanding Mechanical Performance in Reinforced Elastomeric Composite Fibers Using Large Sheets of Graphene Oxide

A simple fiber spinning method used to fabricate elastomeric composite fibers with outstanding mechanical performance is demonstrated. By taking advantage of the large size of as‐prepared graphene oxide sheets (in the order of tens of micrometers) and their liquid crystalline behavior, elastomeric composite fibers with outstanding low strain properties have been fabricated without compromising their high strain properties. For example, the modulus and yield stress of the parent elastomer improved by 80‐ and 40‐fold, respectively, while maintaining the high extensibility of ～400% strain inherent to the parent elastomer. This outstanding mechanical performance was shown to be dependent upon the GO sheet size. Insights into how both the GO sheet size dimension and dispersion parameters influence the mechanical behavior at various applied strains are discussed.     

In Situ Liquid-Cell TEM Observation of Multiphase Classical and Nonclassical Nucleation of Calcium Oxalate

Calcium oxalate (CaOx) is the major phase in kidney stones and the primary calcium storage medium in plants. CaOx can form crystals with different lattice types, water contents, and crystal structures. However, the conditions and mechanisms leading to nucleation of particular CaOx crystals are unclear. Here, liquid-cell transmission electron microscopy and atomistic molecular dynamics simulations are used to study in situ CaOx nucleation at different conditions. The observations reveal that rhombohedral CaOx monohydrate (COM) can nucleate via a classical pathway, while square COM can nucleate via a non-classical multiphase pathway. Citrate, a kidney stone inhibitor, increases the solubility of calcium by forming calcium-citrate complexes and blocks oxalate ions from approaching calcium. The presence of multiple hydrated ionic species draws additional water molecules into nucleating CaOx dihydrate crystals. These findings reveal that by controlling the nucleation pathways one can determine the macroscale crystal structure, hydration state, and morphology of CaOx.     

Differential current conveyor based current comparator

A New differential current conveyor based current comparator is presented in this paper. Differential current conveyor II (DCCII) is designed, modified, and exploited as a comparator with reduced propagation delay and power consumption. New DCCII decreases propagation delay and increases comparator accuracy considerably. Simulation results using Hspice and 0.18 μm CMOS technology with 1.8V supply voltage confirms a less than 0.63 ns propagation delay at ±1 μA input current. Average power dissipation in ±1 μA input current has a value of 300 μW.     

An energy‐efficient and balanced clustering approach for improving throughput of wireless sensor networks

Maximizing the lifespan of wireless sensor networks is currently drawing a lot of attention in the research community. In order to reduce energy consumption, sensor nodes that are far from the base station avoid sending data directly. As a result, several disjoint clusters are formed, and nodes within a cluster send their data through the cluster head to avoid long transmissions. However, several parameters related to transmission cost need to be considered when selecting a cluster head. While most of the existing research work considers energy and distance as the most stringent parameters to reduce energy consumption, these approaches fail to create a fair and balanced cluster. Consequently, unbalanced clusters are formed, resulting in the degradation of overall performance. In this research work, a cluster head selection algorithm is proposed that covers all parts of the sensing area in a balanced manner, saving a significant amount of energy. Furthermore, a capture effect–based intracluster communication mechanism is proposed that efficiently utilizes the time slot under various traffic conditions. A Näive Bayes classifier is used to adapt the window size dynamically according to the traffic pattern. Finally, a simulation model using OMNeT++ is developed to compare the proposed approach with the pioneer clustering approach, LEACH, and the contemporary LEACH‐MAC protocol in terms of performance. The results of the simulation indicate that the proposed approach improves the overall performance in terms of network lifetime, energy efficiency, and throughput.     

Security anomaly detection in software‐defined networking based on a prediction technique

Nowadays, software‐defined networking (SDN) is regarded as the best solution for the centralized handling and monitoring of large networks. However, it should be noted that SDN architecture suffers from the same security issues, which are the case with common networks. As a case in point, one of the shortcomings of SDNs is related to its high vulnerability to distributed denial of service (DDoS) attacks and other similar ones. Indeed, anomaly detection systems have been considered to deal with these attacks. The challenges are related to designing these systems including gathering data, extracting effective features, and selecting the best model for anomaly detection. In this paper, a novel combined approach is proposed; this method uses NetFlow protocol for gathering information and generating dataset, information gain ratio (IGR), in order to select the effective and relevant features and ensemble learning scheme (Stacking) for developing a structure with desirable performance and efficiency for detecting anomaly in SDN environment. The results obtained from the experiments revealed that the proposed method performs better than other methods in terms of enhancing accuracy (AC) and detection rate (DR) and reducing classification error (CE) and false alarm rate (FAR). The AC, DR, CE, and FAR of the proposed model were measured as 99.92%, 99.83%, 0.08%, and 0.03%, respectively. Furthermore, the proposed method prevents the occurrence of excessive overload on the controller and OpenFlow.     

Modelling upper echelons’ behavioural drivers of Green IT/IS adoption using an integrated Interpretive Structural Modelling – Analytic Network Process approach

The purpose of this paper is to understand and identify various psychological drivers which motivate managers of organizations to adopt Green information technology (Green IT) and Green information system (Green IS) within their corporations. These psychological factors are modelled through the lens of Upper Echelon Theory (UET) to study their interrelationship and interdependency and further prioritize them to strategize appropriate managerial actions. The factors were identified through an exhaustive literature review and further confirmed by the experts in the field. A hybrid Interpretive Structural Modelling – Analytic Network Process (ISM-ANP) approach has been adopted to establish the complex interrelationship among the psychological drivers and further to cluster and prioritize them. The main contribution of this study is composing directions and dominance of various psychological drivers to enhance decision-making process of managers towards the adoption of Green IT/IS. As long as decisions are made by individuals within organizations, this paper forms the basis of identifying individual-level factors important in motivating managers towards Green IT/IS adoption. The results of this study would help organizations and policy makers to understand and develop strategies to target and select an individual for managerial position with mind-set more towards environmental sustainability and Green IT/IS concepts. By applying the proposed methodology, organizations can classify and prioritize their action plans such as several educational methods to reinforce, foster and incline psychological factors to motivate their individuals to behave proenvironmentally and practice Green IT/IS initiatives to enhance environmental sustainability of their corporations.     

Public Key Cryptosystem Based on Low Density Lattice Codes

McEliece and Goldreich–Goldwasser–Halevi (GGH) cryptosystems are two instances of code and lattice-based cryptosystems whose security are based on the hardness of coding theoretic and lattice problems, respectively. However, such cryptosystems have a number of drawbacks which make them inefficient in practice. On the other hand, low density lattice codes (LDLCs) are practical lattice codes which can achieve capacity over additive white Gaussian noise channel and also can be encoded and decoded efficiently. This paper introduces a public key cryptosystem based on Latin square LDLCs, by which a relationship can be attained between code and lattice-based cryptography. In this way, we can exploit the efficient properties of codes and lattices, simultaneously to improve the security and efficiency of the proposed scheme. For instance, the security of this scheme is based on the hard problems related to lattices, i.e., closest vector problem and shortest basis problem, which in turn lead to increase the security level. On the other hand, we exploit the low complexity decoding algorithm of LDLCs to reduce the computational complexity. Moreover, this property allows using the larger values of the codeword length. Also, we use the special Gaussian vector, whose variance is upper bounded by Poltyrev bound, as the perturbation (error) vector. These strategies make the proposed scheme to be secure against the conventional cryptanalytic attacks.