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The cost-effective adsorbent was developed to remove copper ions from an aqueous solution. The carbonized sunflower stem was analyzed by SEM, FTIR, and XRD. A batch mode adsorption kinetics study was conducted and was observed that the adsorption of copper ions onto carbonized sunflower stem followed pseudo-second-order kinetics. The equilibrium time was found to be 160 min. Maximum uptake (90 %) of copper ion was observed at pH 3.0 for 20 mg L-1. The experimental data were also analyzed for Langmuir, Freundlich, Dubinin-Radushkevich, and Temkin isotherms.

In the present work, a one-step synthetic method was implemented in an effective way to synthezise aminophenol-modified zinc oxide (Ap-modified ZnO). The as-prepared sample was characterized by various spectral and analytical tools. The electrochemical performance of Ap-modified ZnO demonstrated that the electrode material can be used in supercapacitors. The pronounced capacitive behaviour of Ap-modified ZnO was proved by cyclic voltammetric studies (CV), galvanostatic charge–discharge test (GCD) and electrochemical impedance spectroscopy (EIS) techniques in 1 M H2SO4. The newly developed Ap-modified ZnO electrode displayed an excellent gravimetric capacitance (Cg) of 427 Fg−1 at current density of 1 mA cm−2, which may be attributed to its unique structure, existence of abundant pores and large electroactive sites, supportive for facile electron, ion transport and enhanced electrical conductivity.

Today, we completely rely on Information Technology (IT) applications for every aspect of daily life, including business and online transactions. In addition to using these IT-enabled applications for business purposes, we also use WhatsApp, Facebook, and a variety of other IT applications to communicate with others. However, there will undoubtedly be a drawback to every benefit. Since everything is linked to the Internet, there are many opportunities for security to be compromised. To address this, we are working to identify security threats early on in the software development process, specifically during the requirements phase. During the requirement engineering process, an engineer can recognize the security specifications in a more structured manner to create threat-free software. In our research work, we suggest the Identification of Security Threats during Requirement Engineering (ISTDRE) technique for detecting security risks throughout the requirement engineering process. The four points that make up this ISTDRE technique are Hack Point (HP), Speculation Point (SP), Trust Point (TP), and Reliable Point (RP). The new ISTDRE methodology will be validated using a case study of an ERP system involving two currently used methodologies: Model Oriented Security Requirements Engineering (MOSRE) and System Quality Requirements Engineering (SQUARE).

Data is growing at a rapid rate with ever increasing features and end users. The widespread use of computers and the dramatic evolution in technologies in many large-scale organisations have led to the creation of a number of various application-specific databases to be developed. As organisational systems alter, departmental boundaries move, generating separate sector units. They will use existing data from separate data stores instead of entering the enterprise with new data. The capacity to make data collection interoperable is now becoming a crucial factor in the production of modern information systems. There may be differing degrees of interoperability of data. Commercial gateways bind specific pairs of database management systems to the lowest level (DBMSs). In any case, it is important to have quick access and faster data retrieval.

Smart contracts are set of instructions which are stored on a blockchain. These instructions will be executed automatically without middle-man interaction. Smart contracts in the blockchain allows the transactions and contracts to be executed across undesignated nodes without an interaction of central system or external enforcement. The transactions are transparent, traceable and irreversible. In blockchain all the data stored are secure and immutable. So blockchain would be the suitable environment for smart contracts. Smart contract data is encrypted and placed in a distributed ledger, which means the information stored in the blocks cannot be deleted or modified. There are many blockchain platforms supporting smart contracts. This paper explores the information about various smart contract platforms and its features.

Word sequence prediction is the word processing method that can be very useful for generating text summary by reducing the number of keystrokes when in need for typing words. So, mostly typing and summarizing a large text summary document is very complicated and is time consuming process. With a large and huge amount of data circulating in this digital data world, there is necessary to create and develop some machine learning algorithms that can automatically generate accurate summaries. Types of Neural Network and deep learning field techniques are the most popular and efficient method for automatic text summarization. This paper provides various methods and different datasets that may be used to generate text summaries automatically which reduces the time to manually type and summarize large text documents.

This study proposes a variable step size modified P&O algorithm for active power control (APC) that ensures that a predetermined amount of power, which is less than the maximum power, is extracted from the photovoltaic system without any energy storage. Under varying environmental conditions, the maximum available power varies and care should be taken to ensure that the desired operating point is below and on the right side of the current maximum power point (MPP). This requires real-time estimation of MPP. A neural network (NN)-based MPP estimator is proposed. With NN-based MPP estimator and modified P&O algorithm, a novel APC scheme is shown to perform well under varying environmental and demand conditions. This method of APC has been validated through simulation and experimental results.

AimTo evaluate the impact of couch translational shifts on dose–volume histogram (DVH) and radiobiological parameters [tumour control probability (TCP), equivalent uniform dose (EUD) and normal tissue complication probability (NTCP)] of volumetric modulated arc therapy (VMAT) plans and to develop a simple and swift method to predict the same online, on a daily basis.MethodsIn total, ten prostate patients treated with VMAT technology were selected for this study. The plans were generated using Eclipse TPS and delivered using Clinac ix LINAC equipped with a Millennium 120 multileaf collimator. In order to find the effect of systematic translational couch shifts on the DVH and radiobiological parameters, errors were introduced in the clinically accepted base plan with an increment of 1 mm and up to 5 mm from the iso-centre in both positive and negative directions of each of the three axis, x [right–left (R-L)], y [superior–inferior (S-I)] and z [anterior–posterior (A-P)]. The percentages of difference in these parameters (∆D, ∆TCP, ∆EUD and ∆NTCP) were analyzed between the base plan and the error introduced plans. DVHs of the base plan and the error plans were imported into the MATLAB software (R2013a) and an in-house MATLAB code was generated to find the best curve fitted polynomial functions for each point on the DVH, there by generating predicted DVH for planning target volume (PTV), clinical target volume (CTV) and organs at risks (OARs). Functions f(x, vj), f(y, vj) and f(z, vj) were found to represent the variation in the dose when there are couch translation shifts in R-L, S-I and A-P directions, respectively. The validation of this method was done by introducing daily couch shifts and comparing the treatment planning system (TPS) generated DVHs and radiobiological parameters with MATLAB code predicted parameters.ResultsIt was noted that the variations in the dose to the CTV, due to both systematic and random shifts, were very small. For CTV and PTV, the maximum variations in both DVH and radiobiological parameters were observed in the S-I direction than in the A-P or R-L directions. ∆V70 Gy and ∆V60 Gy of the bladder varied more due to S-I shift whereas, ∆V40 Gy, ∆EUD and ∆NTCP varied due to A-P shifts. All the parameters in rectum were most affected by the A-P shifts than the shifts in other two directions. The maximum percentage of deviation between the TPS calculated and MATLAB predicted DVHs of plans were calculated for targets and OARs and were found to be less than 0·5%.ConclusionThe variations in the parameters depend upon the direction and magnitude of the shift. The DVH curves generated by the TPS and predicted by the MATLAB showed good correlation.

Nature inspired algorithms have been found to be powerful in solving complex optimization problems due to the intelligence embedded in them. Some of these algorithms have also been used in tracking the maximum power point (MPP) in a partially shaded photovoltaic (PV) array. This paper evaluates the capability of five algorithms inspired from nature in tracking maximum power point under partial shading. The performance of the algorithms are compared in terms of their tracking accuracy, convergence time and implementation complexity to find the most suitable method for MPP tracking.

Cloud data centers traditionally use grid energy which emits carbon dioxide and dissipates heat to the environment. To decrease the amount of carbon emissions, many Cloud Service Providers (CSPs) are exploring the possibility of using renewable energy to operate their data centers showing a clear trend to migrate towards green cloud datacenters. Green cloud data centers typically use solar and wind as renewable energy sources. To meet the highly dynamic user demand and to ensure effective power management, an efficient methodology is proposed that performs various load scheduling and power management plans with the integration of renewables for geographically distributed green cloud datacenters. The proposed approach applies nature-inspired Modified Bacterial Foraging Optimization Algorithm (MBFOA) to balance load and reduce eco-aware energy cost. Simulations were conducted to determine the efficacy of the proposed MBFOA algorithm. The algorithm efficiently reduces eco-aware power cost of the system than the baseline methods.

The increase in number of accidents is a dangerous situation that needs to be mitigated. If the data from recent past is taken into account, one can see that the number of road accidents has grown exponentially. In fact, roadways record the highest number of accidents in comparison to other modes of transport. Although drowsy driving is not the only contributor, it remains the principal or major issue and can pose a grave threat if it is not averted. This paper thus aims to introduce a method to reduce the number of accidents due to drowsy driving. Using an Electroencephalograph (EEG) headset which consists of multiple EEG sensors and inbuilt Bluetooth transmitter, brain wave data is transmitted to the system. The collected data is fed as input to the prediction model which decides whether the driver is being drowsy or not. The prediction model is trained by using the Auto Regressive and Integrated Moving Average (ARIMA) time series algorithm to predict whether the person is being drowsy. If so, the proposed system can be used to trigger an alarm/warning mechanism.

A novel terpolymer acts as an effective chelating ion exchanger which was synthesized using 2-amino-6-nitro-benzothiazole and semicarbazide with formaldehyde (BSF) by solution condensation technique. Its ion exchange properties was determined against certain metal ions viz. Fe3+, Co2+, Ni2+, Cu2+, Zn2+ and Pb2+ using batch equilibrium technique with different electrolyte concentrations, pH ranges and time intervals. The results of batch studies revealed that the separation of the selected metal ions from the aqueous solution by the terpolymer is found to be excellent compared to the available commercial resins and earlier reported resins. The order of metal ion uptake at higher concentrations by the BSF terpolymer at lower pH is Cu2+ > Ni2+ > Fe3+ and at lower concentration at higher pH is Zn2+ > Co2+ > Pb2+. The reusability of the resin was also reported for its effective ion-exchange behaviour for several cycles. The adsorption isotherm model was evaluated and the results are in good agreement with each other. The order of kinetics was also determined and the resin follows pseudo-second-order kinetics. Moreover, the physico-chemical analysis gives strong evidence for the effective metal ion removal compared with the earlier reported and commercial resins. Earlier, the structure and the properties of the synthesized novel chelating resin were clearly elucidated by elemental, FTIR, UV–Vis, 1H & 13C NMR spectra, GPC, SEM and XRD.

In the present study, the potential of ZnCl2 activated coir pith carbon for adsorption of phenol from aqueous solution was investigated. Batch kinetics and isotherm studies were carried out to eval...