Near‐infrared transmittance spectroscopy: a potential tool for non‐destructive determination of oil content in groundnuts

The oil content of 64 samples of groundnut kernels, representing 47 genotypes, was determined by the conventional Soxhlet extraction procedure (Oil^SOX). The values of Oil^SOX ranged from 403 to 536 g kg⁻¹. The optical densities (ODs) of these samples were determined at 12 wavelengths (918, 928, 940, 950, 968, 975, 985, 998, 1010, 1023, 1037 and 1045 nm) in the near‐infrared (NIR) region using a food composition analyser (essentially a filter‐based NIR spectrophotometer). The instrument also recorded the temperatures of the sample (Temp^S) and the air (Temp^A) surrounding it. A sample holder (75 mm × 150 mm; optical path length 25 mm) was used for optical density measurement. The data obtained were subjected to multiple linear regression analysis using the ODs at 12 wavelengths, Temp^S and Temp^A as the independent (predictor) variables, and Oil^SOX as the dependent variable. The multiple linear regression equation comprising 14 predictors showed a significant relationship between predicted values of oil content (Oil^NIR) and Oil^SOX. The standard error of calibration and the coefficient of determination for calibration (R) were 3.54 and 0.821 respectively, while the standard error of prediction and the coefficient of determination for prediction were 5.82 and 0.865 respectively. The ratio of standard error of calibration and standard error of prediction was 0.608. The differences between Oil^SOX and Oil^NIR were less than ± 20 g kg⁻¹ for samples having oil contents in the range from 480 to 510 g kg⁻¹. However, for samples having Oil^SOX lower than 480 g kg⁻¹ or higher than 510 g kg⁻¹, differences greater than ± 20 g kg⁻¹ were observed. There exists scope for further refining the regression equation by using a larger number of samples for generating optical data. The results demonstrated the potential of NIR transmittance spectroscopy for determining the oil content of groundnuts in a non‐destructive manner. © 2000 Society of Chemical Industry     

Effects of entrainment and agglomeration of particles on combustion of nano-aluminum and water mixtures

The combustion of nano-aluminum and water mixtures is studied theoretically for a particle size of 80 nm and over a pressure range of 1–10 MPa. Emphasis is placed on the effects of entrainment and agglomeration of particles on the burning rate and its dependence on pressure. The flame thickness increases by a factor of ∼10, when particle entrainment is considered. This lowers the conductive heat flux at the ignition front, thereby reducing the burning rate. The pressure dependence of the burning rate is attributed to the changes in the burning time and velocity of particles with pressure. In the diffusion limit, the pressure exponent increases from 0 to 0.5, when the entrainment index increases from 0 to 1.0. A similar trend is observed in the kinetics-controlled regime, although the corresponding value exceeds the diffusion counterpart by 0.5. The kinetics-controlled model significantly over-predicts the burning rate and its pressure exponent, depending on the entrainment index. The present analysis suggests that nano-particles formed closely-packed agglomerates of diameter 3–5 μm, which may burn under diffusion-controlled conditions at high pressures.     

Effect of packing density on flame propagation of nickel-coated aluminum particles

The combustion-wave propagation of nickel-coated aluminum particles is studied theoretically for packing densities in the range of 10–100% of the theoretical maximum density. Emphasis is placed on the effect of packing density on the burning properties. The energy conservation equation is solved numerically and the burning rate is determined by tracking the position of the flame front. Atomic diffusion coefficients and reaction rate of isolated nickel-coated aluminum particles are input parameters to the model. The burning behaviors and combustion wave structures are dictated by the heat transfer from the flame zone to the unburned region. Five different models for the effective thermal conductivity of the mixture are employed. The impact of radiation heat transfer is also assessed. As a specific example, the case with a particle size of 79 μm is considered in detail. The burning rate remains nearly constant (<1 cm/s) up to a packing density of 60%, and then increases sharply toward the maximum value of 11.55 cm/s at a density of 100%. The Maxwell–Eucken–Bruggeman model of thermal conductivity offers the most accurate predictions of the burning rate for all loading densities.     

Analytical modeling of Transmission Control Protocol NewReno using Generalized Stochastic Petri Nets

This paper presents a novel analytical model of Transmission Control Protocol (TCP) using a generalized stochastic Petri net (GSPN). Extensive simulation work has been done for the performance evaluation of TCP NewReno protocol. In view of the limitations of the simulation technique, we present an analytical approach using GSPN. A GSPN is a useful mathematical tool that solves continuous time Markov chains for complex systems and evaluates the stationary behavior. In this paper, we analyze the slow‐but‐steady variant of TCP NewReno. The model captures the behavioral aspects of the slow start and the congestion avoidance phase together with the fast retransmit and recovery capabilities of TCP NewReno. Performance metrics such as throughput, goodput, and task completion time of the system are obtained. The effect of variation in the model parameters on the performance is studied. The results are validated using the network simulator, and their accuracy is verified by evaluating the confidence interval. The performance of the proposed model is compared with that of TCP Reno. The performance of the proposed model is also compared with one of the previous models. The numerical illustrations and comparison of the proposed technique with simulation validates the accuracy, efficiency, and competence of the GSPN technique. While GSPN modeling for TCP is investigated in depth for the TCP NewReno and TCP Reno variant in this paper, other protocols could be also analyzed similarly. Copyright © 2013 John Wiley & Sons, Ltd.     

Multicast Network Security with Asymmetric Cooperative Relaying

International Journal of Wireless Information Networks - This paper exhibits the confidentiality performance study of a cooperative multicast network consisting of $${\mathcal {K}}$$ asymmetric...     

Encrypted Network Traffic Classification and Resource Allocation with Deep Learning in Software Defined Network

Wireless Personal Communications - The climate has changed absolutely in every area in just a few years as digitized, making high-speed internet service a significant need in the future. Future...     

Cloud Security Service for Identifying Unauthorized User Behaviour

Recently, an innovative trend like cloud computing has progressed quickly in Information Technology. For a background of distributed networks, the extensive sprawl of internet resources on the Web and the increasing number of service providers helped cloud computing technologies grow into a substantial scaled Information Technology service model. The cloud computing environment extracts the execution details of services and systems from end-users and developers. Additionally, through the system’s virtualization accomplished using resource pooling, cloud computing resources become more accessible. The attempt to design and develop a solution that assures reliable and protected authentication and authorization service in such cloud environments is described in this paper. With the help of multi-agents, we attempt to represent Open-Identity (ID) design to find a solution that would offer trustworthy and secured authentication and authorization services to software services based on the cloud. This research aims to determine how authentication and authorization services were provided in an agreeable and preventive manner. Based on attack-oriented threat model security, the evaluation works. By considering security for both authentication and authorization systems, possible security threats are analyzed by the proposed security systems.     

Deep packet inspection using parallel bloom filters

There is a class of packet processing applications that inspect packets deeper than the protocol headers to analyze content. For instance, network security applications must drop packets containing certain malicious Internet worms or computer viruses carried in a packet payload. Content forwarding applications look at the hypertext transport protocol headers and distribute the requests among the servers for load balancing. Packet inspection applications, when deployed at router ports, must operate at wire speeds. With networking speeds doubling every year, it is becoming increasingly difficult for software-based packet monitors to keep up with the line rates. We describe a hardware-based technique using Bloom filters, which can detect strings in streaming data without degrading network throughput. A Bloom filter is a data structure that stores a set of signatures compactly by computing multiple hash functions on each member of the set. This technique queries a database of strings to check for the membership of a particular string. The answer to this query can be false positive but never a false negative. An important property of this data structure is that the computation time involved in performing the query is independent of the number of strings in the database provided the memory used by the data structure scales linearly with the number of strings stored in it. Furthermore, the amount of storage required by the Bloom filter for each string is independent of its length.