Live video streaming service with pay-as-you-use model on Ethereum Blockchain and InterPlanetary file system

Wireless Networks - In centralized video streaming platforms, the platform owner, rather than the content producer, controls most of the content uploaded on the centralized video...     

Phosphorus- and silicon-containing amino curing agent for epoxy resin

Iranian Polymer Journal - Current research work focuses on the synthesis of phosphorus- and silicon-containing amine curing agent (PSA) for epoxy resins. PSA was synthesized using phenyl phosphonic...     

Characterization of Waste and Reclaimed Green Sand Used in Foundry Processing

Silicon - The aim of this study is to discuss the importance of characterization of green, waste green and reclaimed sand. The transformations and changes which take place in the green sand, are...     

Hydrothermal synthesis of α-SnWO4: Application to lithium-ion battery and photocatalytic activity

The high capacity anode material is required to replace the most commonly used anode - graphite to keep up the global demand to achieve the goal. Multi-metal oxide has gained keen attention for its higher theoretical capacity and relatively stable than a single metal oxide. α-SnWO₄ has a theoretical capacity of 850 mAh g^?1 which is greater than graphite (372 mAh g^?1). α-SnWO₄ has been synthesized through low-temperature hydrothermal method using tin chloride and sodium tungstate as a precursor in acidic medium (succinic acid) at 200 °C for 12 h. The obtained product has been characterized using various analytical tools such as XRD, FT-IR, UV-DRS, BET, PL, SEM, and HR-TEM. XRD analysis shows the orthorhombic phase with a crystallite size of ~25 nm α-SnWO₄has been examined as an electrode material for Li-ion battery (LIB) and displays an initial discharge capacity of 985 mAh g^?1. Columbic efficiency close to 100% has been observed for 100 cycles. The stability of the electrode material was studied at different C-rates. Band-gap calculated using UV-DRS (Eg = 1.9 eV) shows that α-SnWO₄ is a good candidate for photocatalytic degradation. Results of the photocatalytic experiment using methylene blue (MB) as a model pollutant in an aqueous medium shows good results. The above applications show that α-SnWO₄ is multifunctional materials for diverse applications.     

Novel catechol-derived phosphorus-based precursors for coating applications

Polymer Bulletin - Depletion of the petroleum resources and poor flame-retardant properties of the epoxy resins drive researchers to develop an epoxy resin with good heat stability from...     

Varna-based optimization:a novel method for capacitated controller placement problem in SDN

Recently,software defined networking(SDN)is a promising paradigm shift that decouples the control plane from the data plane.It can centrally monitor and control the network through softwarization,i.e.,controller.Multiple controllers are a necessity of current SDN based WAN.Placing multiple controllers in an optimum way is known as controller placement problem(CPP).Earlier,solutions of CPP only concentrated on propagation latency but overlooked the capacity of controllers and the dynamic load on switches,which is a significant factor in real networks.In this paper,we develop a novel optimization algorithm named varna-based optimization(VBO)and use it to solve CPP.To the best of our knowledge,this is the first attempt to minimize the total average latency of SDN along with the implementation of TLBO and Jaya algorithms to solve CPP for all twelve possible scenarios.Our experimental results show that TLBO outperforms PSO,and VBO outperforms TLBO and Jaya algorithms in all scenarios for all topologies.     

Segregation and intermixing in polydisperse liquid–solid fluidized beds: A multifluid model validation study

Multifluid model (MFM) simulations have been carried out on liquid–solid fluidized beds (LSFB) consisting of binary and higher-order polydisperse particle mixtures. The role of particle–particle interactions was found to be as crucial as the drag force under laminar and homogenous LSFB flow regimes. The commonly used particle–particle closure models are designed for turbulent and heterogeneous gas–solid flow regimes and thus exhibit limited to no success when implemented for LSFB operating under laminar and homogenous conditions. A need is perceived to carry out direct numerical simulations of liquid–solid flows and extract data from them to develop rational closure terms to account for the physics of LSFB. Finally, a recommendation flow regime map signifying the performance of the MFM has been proposed. This map will act as a potential guideline to identify whether or not the bed expansion characteristics of a given polydisperse LSFB can be correctly simulated using MFM closures tested.     

A multilevel hybrid anomaly detection scheme for industrial wireless sensor networks

Real-time sensing plays an important role in ensuring the reliability of industrial wireless sensor networks (IWSNs). Sensor nodes in IWSNs have inherent limitations that give rise to different anomalies in the network. These anomalies can lead to disastrous and harmful situations or even serious system failures. This article presents a formulation to the design of an anomaly detection scheme for detecting the anomalous node along with the type of anomaly. The proposed scheme is divided into two major parts. First, spatiotemporal correlation within a cluster is obtained for the normal and anomalous behavior of sensor nodes. Second, the multilevel hybrid classifier is used by combining the sequential minimal optimization support vector machine (SMO-SVM) as a binary classifier with optimally pruned extreme learning machine (OP-ELM) as a multiclass classifier for detection of an anomalous node and type of anomalies, respectively. Mahalanobis distance-based lightweight K-Medoid clustering is used to build a new set of training datasets that represents the original training dataset, by significantly reducing the training time of a multilevel hybrid classifier. Results are analyzed using standard WSN datasets. The proposed model shows high accuracy, i.e., 94.79% and detection rate, i.e., 94.6% with a reduced false positive rate as compared to existing hybrid methods.     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

Direct three dimensional tomography of flames using maximization of entropy technique

Presently, there are numerous applications for non-destructive techniques like emission tomography, laser based methods and particle image velocimetry that are used to study flame characteristics. Reconstruction of the flame intensity field using emission tomography has the advantage over other technologies that it gives accurate results but at the same time requires relatively inexpensive equipment, and therefore, has numerous industrial applications. In the present paper, a new algorithm performing Direct-3D reconstruction using the maximization of entropy (MENT) methodology has been introduced. Through detailed studies using a mathematical object, it has been shown that the Direct-3D algorithm shows significantly reduced errors as compared to 2D slice-by-slice reconstruction algorithms. Secondly, the major features of the proposed algorithm, for e.g., effect of orientation, effect of number of views, and robustness have been discussed. Finally, a few qualitative results from actual flames have been presented using a candle and a gas fired burner, and the results match well with the actual flame geometry and intensity distribution.