A novel social deep autoencoder NMF incentive scheme to detect a selfish node in delay tolerant network

Detection of the selfish node in a delay tolerant network (DTN) can sharply reduce the loss incurred in a network. The algorithm's current pedigree mainly focuses on the rely on nodes, records, and delivery performance. The community structure and social aspects have been overlooked. Analysis of individual and social tie preferences results in an extensive detection time and increases communication overhead. In this article, a heterogeneous DTN topology with high-power stationary nodes and mobile nodes on Manhattan's accurate map is designed. With the increasing complexity of social ties and the diversified nature of topology structure, there need for a method that can effectively capture the essence within the speculated time. In this article, a novel deep autoencoder-based nonnegative matrix factorization (DANMF) is proposed for DTN topology. The topology of social ties projected onto low-dimensional space leads to effective cluster formation. DANMF automatically learns an appropriate nonlinear mapping function by utilizing the features of data. Also, the inherent structure of the deep autoencoder is nonlinear and has strong generalization. The membership matrices extracted from the DANMF are used to design the weighted cumulative social tie that eventually, along with the residual energy, is used to detect the network's selfish node. The testing of the designed model is carried out on the real dataset of MIT reality. The proficiency of the developed algorithm has been well tested and proved at every step. The methods employed for social tie extraction are NMF and DANMF. The methodology is rigorously experimented on various scenarios and has improved around 80% in the worst-case scenario of 40% nodes turning selfish. A comprehensive comparison is made with the other existing state-of-the-art methods which are also incentive-based approaches. The developed method has outperformed and has shown the supremacy of the current methods to capture the latent, hidden structure of the social tie.

     

CanarDeep: a hybrid deep neural model with mixed fusion for rumour detection in social data streams

Neural Computing and Applications - The unrelenting trend of doctored narratives, content spamming, fake news and rumour dissemination on social media can lead to grave consequences that range from...     

Incorporating linear programing and life cycle thinking into environmental sustainability decision-making: a case study on anchovy canning industry

Life cycle assessment (LCA) is a powerful tool to support environmental informed decisions among product and process alternatives. LCA results reflect the process stage contributions to several environmental impacts, which should be made mutually comparable to help in the decision-making process. Aggregated environmental indexes enable the translation of this set of metrics into a one final score, by defining the attached weights to impacts. Weighting values reflect the corresponding relevance assigned to each environmental impact. Current weighing schemes are based on pre-articulation of preferences, without considering the specific features of the system under study. This paper presents a methodology that combines LCA methodology and linear programming optimisation to determine the environmental improvement actions that conduct to a more sustainable production. LCA was applied using the environmental sustainability assessment methodology to obtain two main indexes: natural resources (NR) and environmental burdens (EB). Normalised indexes were optimised to determine the optimal joint of weighting factors that lead to an optimised global Environmental Sustainability Index. The proposed methodology was applied to a food sector, in particular, to the anchovy canning industry in Cantabria Region (Northern Spain). By maximising the objective function composed of NR and EB variables, it is possible to find the optimal joint of weights that identify the best environmental sustainable options. This study proves that LCA can be applied in combination with linear programing tools as a part of the decision-making process in the development of more sustainable processes and products.     

A mathematical model for wave propagation in a composite solid matrix containing two immiscible fluids

Constitutive relations and field equations have been extended for a porous medium composed of two solids and containing two chemically non-reactive immiscible fluids. By generalizing the closure relation of porosity change and employing this into the mass balance equations, the stress–strain relations have been developed. The idea of generalized compressibility tests is invoked to find the value of dimensionless parameters appearing in the closure relation of porosity change. By generalizing momentum balance equations of Lo et al. (Water Resour Res 41:1–20, 2005), the propagation of dilatational and rotational waves is explored. It is found that four dilatational and two rotational waves exist in the porous medium. In contrast to Biot’s theory, the presence of the second fluid and second solid in the porous medium gives rise to additional P- and S-waves. Variation of phase speeds and corresponding attenuation coefficients of existing waves versus frequency, saturation of the fluid phases and solid fraction are computed numerically and depicted graphically.     

Mechanical and Thermophysical Properties of Cerium Monopnictides

The ultrasonic attenuation due to phonon–phonon interaction, thermoelastic relaxation and dislocation damping mechanisms has been investigated in cerium monopnictides CeX (X: N, P, As, Sb and Bi) for longitudinal and shear waves along \({\langle }100{\rangle }\), \({\langle }110{\rangle }\) and \({\langle }111{\rangle }\) directions. The second- and third-order elastic constants of CeX have also been computed in the temperature range 0 K to 500 K using Coulomb and Born–Mayer potential upto second nearest neighbours. The computed values of these elastic constants have been applied to find out Young’s moduli, bulk moduli, Breazeale’s non-linearity parameters, Zener anisotropy, ultrasonic velocity, ultrasonic Grüneisen parameter, thermal relaxation time, acoustic coupling constants and ultrasonic attenuation. The fracture/toughness ratio is less than 1.75, which shows that the chosen materials are brittle in nature as found for other monopnictides. The drag coefficient acting on the motion of screw and edge dislocations due to shear and compressional phonon viscosities of the lattice have also been evaluated for both the longitudinal and shear waves. The thermoelastic loss and dislocation damping loss are negligible in comparison to loss due to Akhieser damping (phonon–phonon interaction). The obtained results for CeX are in qualitative agreement with other semi-metallic monopnictides.     

An improved harmony search algorithm with dynamically varying bandwidth

The present work demonstrates a new variant of the harmony search (HS) algorithm where bandwidth (BW) is one of the deciding factors for the time complexity and the performance of the algorithm. The BW needs to have both explorative and exploitative characteristics. The ideology is to use a large BW to search in the full domain and to adjust the BW dynamically closer to the optimal solution. After trying a series of approaches, a methodology inspired by the functioning of a low-pass filter showed satisfactory results. This approach was implemented in the self-adaptive improved harmony search (SIHS) algorithm and tested on several benchmark functions. Compared to the existing HS algorithm and its variants, SIHS showed better performance on most of the test functions. Thereafter, the algorithm was applied to geometric parameter optimization of a friction stir welding tool.     

Physiatric research fellows'' perceptions of the quality of their training

After being poisoned by eating the mushroom species Cortinarius speciosissimus, a twin developed interstitial nephritis with acute renal failure. He received a renal transplant from his living twin brother, who was presumed dizygotic on phenotypic grounds. Fifteen years later, the twins were zygosity tested by DNA "fingerprint analysis" and found to be monozygotic, despite important phenotypic discordances. The recipient has discontinued immunosuppression therapy and remains well after 9 months. We suggest that, for medical and other reasons, zygosity should be determined at birth on all like-sexed twins.     

PVC-Based 2,2,2-Cryptand Sensor for Zinc Ions

A PVC-based membrane of 2,2,2-cryptand exhibits a very good response for Zn(2+) in a wide concentration range (from 2.06 ppm to 6.54 × 10(3) ppm) with a slope of 22.0 mV/decade of Zn(2+) concentration. The response time of the sensor is <10 s, and the membrane can be used for more than 3 months without any observed divergence in potentials. The proposed sensor exhibits very good selectivity for Zn(2+) over other cations and can be used in a wide pH range (2.8-7.0). It has also been possible to use this assembly as an indicator electrode in potentiometric titrations involving zinc ions.     

Graph theoretic foundations of multibody dynamics

This second part of a two part paper uses concepts from graph theory to obtain a deeper understanding of the mathematical foundations of multibody dynamics. The first part (Jain in Graph theoretic foundations of multibody dynamics. Part I. Structural properties, 2010) established the block-weighted adjacency (BWA) matrix structure of spatial operators associated with serial- and tree-topology multibody system dynamics, and introduced the notions of spatial kernel operators (SKO) and spatial propagation operators (SPO). This paper builds upon these connections to show that key analytical results and computational algorithms are a direct consequence of these structural properties and require minimal assumptions about the specific nature of the underlying multibody system. We formalize this notion by introducing the notion of SKO models for general tree-topology multibody systems. We show that key analytical results, including mass-matrix factorization, inversion, and decomposition hold for all SKO models. It is also shown that key low-order scatter/gather recursive computational algorithms follow directly from these abstract-level analytical results. Application examples to illustrate the concrete application of these general results are provided. The paper also describes a general recipe for developing SKO models. The abstract nature of SKO models allows for the application of these techniques to a very broad class of multibody systems.