A new region aware invisible robust blind watermarking approach

Multimedia Tools and Applications - The multimedia revolution has made a strong impact on our society. The explosive growth of Internet access to this digital information has generated new...     

Influence of B-site cations ordering on magnetization and dielectric relaxations in Li–Ni spinel ferrites

Ho-substituted Li–Ni ferrites with composition L i_1.2Ni_0.4Ho_xFe_2-xO₄; 0≤ x ≤ 0.15 were synthesized by a self-ignited sol-gel process. An annealing temperature of 950 °C is estimated via thermal-gravimetric (TGA) analysis. X-ray diffraction (XRD) scans have confirmed the formation of the ferrite phase with a spinel structure in all samples. Substitution of Ho ions on the B-site significantly reduced the porosity from 38 -to 23% and the crystallite size from 23.4 -to 21.7 nm. Microstructural analysis revealed a denser structure with an increase in Ho content. Dielectric results showed that both the dielectric loss and dielectric constant depict a nonlinear variation with the addition of Ho. Complex impedance behavior with a single semicircle for all samples suggests the predominant effect of the grain boundary mechanism. The substitution of Ho ions in place of Fe ions significantly decreased the electrical conductivity. The anisotropic Ho³⁺ ions reinforce the L-S coupling which consequently enhanced the coercive force from 145 -to 389 Oe, and thus the anisotropy constant.     

An economic model predictive control approach to integrated production management and process operation

Managing production schedules and tracking time‐varying demand of certain products while optimizing process economics are subjects of central importance in industrial applications. We investigate the use of economic model predictive control (EMPC) in tracking a production schedule. Specifically, given that only a small subset of the total process state vector is typically required to track certain scheduled values, we design a novel EMPC scheme, through proper construction of the objective function and constraints, that forces specific process states to meet the production schedule and varies the rest of the process states in a way that optimizes process economic performance. Conditions under which feasibility and closed‐loop stability of a nonlinear process under such an EMPC for schedule management can be guaranteed are developed. The proposed EMPC scheme is demonstrated through a chemical process example in which the product concentration is requested to follow a certain production schedule. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1892–1906, 2017     

A feedback control framework for safe and economically‐optimal operation of nonlinear processes

Maintaining safe operation of chemical processes and meeting environmental constraints are issues of paramount importance in the area of process systems and control engineering, and are ideally achieved while maximizing economic profit. It has long been argued that process safety is fundamentally a process control problem, yet few research efforts have been directed toward integrating the rather disparate domains of process safety and process control. Economic model predictive control (EMPC) has attracted significant attention recently due to its ability to optimize process operation accounting directly for process economics considerations. However, there is very limited work on the problem of integrating safety considerations in EMPC to ensure simultaneous safe operation and maximization of process profit. Motivated by the above considerations, this work develops three EMPC schemes that adjust in real‐time the size of the safety sets in which the process state should reside to ensure safe process operation and feedback control of the process state while optimizing economics via time‐varying process operation. Recursive feasibility and closed‐loop stability are established for a sufficiently small EMPC sampling period. The proposed schemes, which effectively integrate feedback control, process economics, and safety considerations, are demonstrated with a chemical process example. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2391–2409, 2016     

Intermittent sensor fault detection for stochastic LTV systems with parameter uncertainty and limited resolution

ABSTRACT

This paper considers the detection problem of intermittent sensor faults in stochastic linear time-varying systems with both parameter uncertainty and limited resolution. By introducing the soft measurement model, a state estimator is designed whose upper bound of estimation error covariance is obtained and minimised at each time step. Based on it, the residual is generated and its relationship with the fault is analysed quantitatively. Then the evaluation function and corresponding detection threshold is given. Our proposed method is recursive and therefore suitable for real-time online applications. At last, two simulation studies are carried out to illustrate the validity of our proposed method.     

Economic model predictive control of stochastic nonlinear systems

This work focuses on the design of stochastic Lyapunov‐based economic model predictive control (SLEMPC) systems for a broad class of stochastic nonlinear systems with input constraints. Under the assumption of stabilizability of the origin of the stochastic nonlinear system via a stochastic Lyapunov‐based control law, an economic model predictive controller is proposed that utilizes suitable constraints based on the stochastic Lyapunov‐based controller to ensure economic optimality, feasibility and stability in probability in a well‐characterized region of the state‐space surrounding the origin. A chemical process example is used to illustrate the application of the approach and demonstrate its economic benefits with respect to an EMPC scheme that treats the disturbances in a deterministic, bounded manner. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3312–3322, 2018     

Effect of silver (Ag) ions irradiation on the structural,optical and photovoltaic properties of Mn doped TiO2 thin films based dye sensitized solar cells

Dye sensitized solar cell (DSSC) is an emerging energy harvesting tool which converts direct sunlight into electrical energy. These cells have much better properties in contrast with silicon based solar cells because of their flexible nature, light weight, low cost, environment friendly nature, and involvement of a simple manufacturing process. Since, a photoanode is the backbone of DSSC, we synthesized a pure and 1% manganese (Mn) doped titanium dioxide (TiO₂) films by sol-gel method which are irradiated with silver (Ag) ions at two different concentrations (2 × 10¹⁴ and 4 × 10¹⁴) ions-cm^?2. X-ray diffraction revealed that Mn doping followed by Ag irradiation transformed TiO₂ from pure anatase to rutile phase. Ultraviolet–visible spectroscopy exposed the reduction in band gap of TiO₂ film during this doping and irradiation process. Therefore, absorption is enhanced with red shift in UV-range. When these films are used as a photoanode in DSSC, 1% Mn doped TiO₂ film exposed with Ag at the concentration of (2 × 10¹⁴) ions-cm^?2 exhibited maximum efficiency of 2.40%.     

Distributed economic model predictive control for operational safety of nonlinear processes

Achieving operational safety of chemical processes while operating them in an economically‐optimal manner is a matter of great importance. Our recent work integrated process safety with process control by incorporating safety‐based constraints within model predictive control (MPC) design; however, the safety‐based MPC was developed with a centralized architecture, with the result that computation time limitations within a sampling period may reduce the effectiveness of such a controller design for promoting process safety. To address this potential practical limitation of the safety‐based control design, in this work, we propose the integration of a distributed model predictive control architecture with Lyapunov‐based economic model predictive control (LEMPC) formulated with safety‐based constraints. We consider both iterative and sequential distributed control architectures, and the partitioning of inputs between the various optimization problems in the distributed structure based on their impact on process operational safety. Moreover, sufficient conditions that ensure feasibility and closed‐loop stability of the iterative and sequential safety distributed LEMPC designs are given. A comparison between the proposed safety distributed EMPC controllers and the safety centralized EMPC is demonstrated via a chemical process example. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3404–3418, 2017     

Graphitic Carbon Nitride Decorated with Iron Oxide Nanoparticles as a Novel High-Performance Biomimetic Electrochemical Sensing Platform for Paracetamol Detection

Design and development of new generation smart sensors for medical applications have gained considerable interest of research community in the recent past. In this work, we propose the fabrication of highly sensitive paracetamol sensors-based iron oxide nanoparticles intercalated with graphitic carbon nitride (g-C₃N₄) (GCN) via insitu chemical synthesis. Structural features of the composites were analyzed through SEM, EDX, XRD, FTIR, and UV-Visible spectroscopic techniques. Presence of iron oxide nanoparticles in GCN, significantly improved the conductivity bare GCN from 16 to 125 S cm^?1 due to extended π–π conjugation and large surface area in the composite system. The GCN-Iron oxide (GCN-FO) nanocomposite has been employed as an electrochemical sensing platform for non-enzymatic detection of paracetamol. The electrochemical studies and cyclic voltammetry (CV) results shows that the GCN-FO composite exhibit superior electrochemical properties due to their lower values of the oxidation and reduction potentials. Electrochemical impedance spectroscopy (EIS) studies indicate decreased charge-transfer resistance for iron oxide doped GCN composite in compare to base GCN. The improved electrochemical sensing performance of modified GCN-FO composite electrode is attributed to the formation heterojunctions between iron oxide nanoparticles and GCN. The modified GCN-FO electrodes were employed for non-enzymatic electrochemical detection of PR. The GCN-FO composite electrode shows excellent sensitivity towards PR with a LOD 0.3 μM. Furthermore, the modified GCN-FO electrodes show excellent reproducibility, selectivity, stability and anti-interference performance. Due to its low-cost fabrication, superior electrochemical sensing performance, these modified GCN-FO electrodes could be a promising material for the detection of paracetamol at low concentrations.

     

Energy-efficient and Secure Wireless Communication for Telemedicine in IoT

The Internet of Things (IoT) represents a radical shifting paradigm for technological innovations as it can play critical roles in cyberspace applications in various sectors, such as security, monitoring, medical, and environmental sectors, and also in control and industrial applications. The IoT in E-medicine unleashed the design space for new technologies to give instant treatment to patients while also monitoring and tracking health conditions. This research presents a system-level architecture approach for IoT energy efficiency and security. The proposed architecture includes functional components that provide privacy management and system security. Components in the security function group provide secure communications through Multi-Authority Ciphertext-Policy Attributes-Based Encryption (MA-CPABE). Because MA-CPABE is assigned to unlimited devices, presuming that the devices are reliable, the user encodes data with Advanced Encryption Standard (AES) and protects the ABE approach using the solutions of symmetric key. The Johnson’s algorithm with a new computation measure is used to increase network lifetime since an individual sensor node with limited energy represents the inevitable constraints for the broad usage of wireless sensor networks. The optimal route from a source to destination turns out as the cornerstone for longevity of network and its sustainability. To reduce the energy consumption of networks, the evaluation measures consider the node’s residual energy, the number of neighbors, their distance, and the link dependability. The experiment results demonstrate that the proposed model increases network life by about 12.25% (27.73%) compared to Floyd–Warshall’s, Bellman–Ford’s, and Dijkstra’s algorithms, lowering consumption of energy by eliminating the necessity for re-routing the message as a result of connection failure.