Self-assembled biogenic melanin modulated surface chemistry of biopolymers-colloidal silica composite porous matrix for the recovery of uranium

A new composite porous matrix surface modulated by self-assembled melanin was developed and investigated for its affinity to bind uranium from an aqueous medium. The composite matrix was synthesized using biopolymers (i.e., agarose and alginate) and inorganic colloidal silica nanoparticles (AACS) by the process of cryotropic-gelation at subzero-temperature. Post-synthesis surface modification of AACS matrix with melanin (MAACS) was performed by green chemistry. The in situ sequestrial conversion of l -Dopa by the biocatalytic activity of tyrosinase enzyme allows the formation of melanin on the surface of AACS matrix. The functional moieties on the matrix display fast kinetics and high binding capacity with respect to uranium. MAACS matrix showed high porosity (~90%) with interconnected pores, high swelling kinetics and permeability. Other physicochemical properties of the matrix, such as thermal stability, storage modulus, and surface charge potential were found to be increased, while percent degradation decreased, which demonstrate improved properties of the matrix after impregnation of silica nanoparticles and surface functionalization with melanin. Thermodynamic parameters suggest that the binding of uranyl ions is passive and spontaneous. The concentrated recovery of uranium was achieved with reusability potential of adsorbent. These results suggest an environment friendly and safer method for the recovery of uranium. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 46937.     

Detecting stealth DHCP starvation attack using machine learning approach

Dynamic Host Configuration Protocol (DHCP) is used to automatically configure clients with IP address and other network configuration parameters. Due to absence of any in-built authentication, the protocol is vulnerable to a class of Denial-of-Service (DoS) attacks, popularly known as DHCP starvation attacks. However, known DHCP starvation attacks are either ineffective in wireless networks or not stealthy in some of the network topologies. In this paper, we first propose a stealth DHCP starvation attack which is effective in both wired and wireless networks and can not be detected by known detection mechanisms. We test the effectiveness of proposed attack in both IPv4 and IPv6 networks and show that it can successfully prevent other clients from obtaining IP address, thereby, causing DoS scenario. In order to detect the proposed attack, we also propose a Machine Learning (ML) based anomaly detection framework. In particular, we use some popular one-class classifiers for the detection purpose. We capture IPv4 and IPv6 traffic from a real network with thousands of devices and evaluate the detection capability of different machine learning algorithms. Our experiments show that the machine learning algorithms can detect the attack with high accuracy in both IPv4 and IPv6 networks.     

A bi-objective task scheduling approach in fog computing using hybrid fireworks algorithm

The Journal of Supercomputing - With the rapid increase in the functionality of IoT applications, the services provided by edge/IoT devices have surged in the recent past. Fog computing is gaining...     

Dual segment rectangular dielectric resonator antenna with metamaterial for improvement of bandwidth and gain

The simulation and experimental studies of an aperture‐coupled wideband dual segment rectangular dielectric resonator antenna with metamaterial for C‐band applications are presented in this paper. The antenna consists of Alumina (Al₂O₃) ceramic as upper segment and Teflon as lower segment. The combination of circular‐shaped coplanar split‐ring resonator and conducting strip has been used as metamaterial superstrate. With the use of metamaterial superstrate, the bandwidth of the antenna is increased by 48% through simulation and 22% experimentally. The broadside radiation pattern of the antenna is converted into directive radiation pattern with reduced beamwidth when metamaterial superstrate is used. The peak gain of the antenna is also enhanced by 33% through simulation and 31% experimentally with the use of metamaterial superstrate. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:646–655, 2014.     

Development of spectral band cloning techniques for soil nutrients estimation

Satellite‐based monitoring is an indispensable tool to guide soil‐specific crop management. However, it has attained little success in the estimation of soil nutrients due to the limitations incurred from inherent spectral characteristics. In this study, spectral band cloning (SBC) is developed and proposed to augment the soil nutrient predictive capabilities of broadband satellite data. Fine‐spectral channels of spectrometers were synchronized with coarse resolution of IRS satellite data to generate nutrient‐sensitive cloned IRS bands. Soil samples, collected at the time of satellite image acquisition in Lop Buri, Thailand, were analyzed both spectrally and chemically, viz., soil organic matter (OM), phosphorus, potassium and iron. The resulting SBC‐based models showed acceptable correlations, which otherwise were unattainable from raw IRS bands through prevailing models. Accuracy and validation measures showed good agreements between the measured and estimated nutrient surfaces. It is concluded that the SBC is a promising method of quantitative soil nutrient mapping, and could further be used for identification and mapping of other indiscernible biophysical parameters.     

Effect of laser irradiation on the electrical properties of amorphous germanium films

Amorphous films of germanium were grown using a vacuum evaporation technique, on glass substrates kept at room temperature. As-grown films were irradiated with Q-Switched Nd-YAG laser pulses (=1.06 m, 20nsec, 10 to 50Jcm^–2). The d.c. conductivity measurements were made in the temperature range 77 to 300 K. It was observed that the effect of laser irradiation was similar to the effect caused by the thermal annealing of the films. The d.c. conductivity data were analysed in the light of Mott's theory of a variable range hopping conduction process.     

Performance analysis of long-lived transaction processing systemswith rollbacks and aborts

Increasing the parallelism in transaction processing and maintaining data consistency appear to be two conflicting goals in designing distributed database systems (DDBSs). This problem is especially difficult if the DDBS is serving long-lived transactions (LLTs). A special case of LLTs, called sagas, has been introduced that addresses this problem. A DDBS with sagas provides high parallelism to transactions by allowing sagas to release their locks as early as possible. However, it is also subject to an overhead, due to the efforts needed to restore data consistency in the case of failure. We conduct a series of simulation studies to compare the performance of LLT systems with and without saga implementation in a faulty environment. The studies show that saga systems outperform their nonsaga counterparts under most of conditions, including heavy failure cases. We thus propose an analytical queuing model to investigate the performance behavior of saga systems. The development of this analytical model assists us to quantitatively study the performance penalty of a saga implementation due to the failure recovery overhead. Furthermore, the analytical solution can be used by system administrators to fine-tune the performance of a saga system. This analytical model captures the primary aspects of a saga system, namely data locking, resource contention and failure recovery. Due to the complicated nature of the analytical modeling, we solve the model approximately for various performance metrics using decomposition methods, and validate the accuracy of the analytical results via simulations     

IE2M: Design of intellectual energy efficient multicast routing protocol for ad-hoc network

In this paper, an intellectual energy efficient multicast routing protocol is proposed. It achieves enhanced performance over On-Demand Multicast Routing Protocol (ODMRP). The proposed protocol finds energy efficient multicast routes from source node to a group of receivers. Multicast mesh creation involves two phases: a Join Query (J-Q) phase and a Join Reply (J-R) phase. The J-Q phase initiates a route discovery process to find routes of the multicast group. In J-R phase, different routes of the multicast groups are set up. In the proposed protocol, we modify ODMRP and introduce fuzzy inference system to deal with imprecise and partial information during the route discovery phase. The decision maker uses two fuzzy variables such as energy and distance for evaluating reward as an output parameter of each multicast route. This output parameter helps to distinguish different multicast route and it also helps to reduce the effect of mutual interference between routes. The proposed protocol is simulated using the NS-2 simulator. The performance of the proposed protocol is compared with existing multicast routing protocols, and results outperform existing protocols in terms of several network metrics.