Progress on the boundary element method to study the disturbance fields of bodies moving in an unbounded medium

For studying flow problems involved with complex physics it is now common to use numerical field methods for solving Navier-Stokes or Euler equations. However, for a large class of fluid mechanics problems, which can be dealt with linearized potential equations, the boundary element method proves to be quite useful, especially for its easy application and relatively less computational effort compared to the field methods. The boundary element method has undergone some significant advancements in the last decade with respect to the study of steady and unsteady flow problems concerning wing aerodynamics in compressible medium, flow fields of propellers and rotors and acoustical disturbance propagation from moving bodies. In this paper a few recent contributions which evolved in the DLR as research projects and as doctoral and diploma thesis of the Technical University Braunschweig are concisely described.List of symbols a Sound velocity - b Span of a wing - c _p Coefficient of static pressure - c _dp Coefficient of profile drag - c ₁, c _d, c_m Coefficient of lift, drag and moment per unit span width - c _L, c_D, c_M Total lift, drag and moment-coefficients - c _T, c_P Thrust and power-coefficient of a propeller - d Distance - D Doublet strength - e Specific heat energy - E Total energy in a moving medium element - f Frequency - F Field point - g Gravitational acceleration - h Radial distance in cylinder coordinates - I ₁, I ₂ Inducing functions - i, j, k Unit vectors in cartesian coordinates - k Wave number [/a ] - l Local wing-chord - l ₀, l _v Length of singularity element at t _oand t _v - m Notation for Fourier-component - M, M ^* Mach number based on local and critical sound speed - n Number of rotation per second - n Unit normal vector to a surface     

Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO2 emissions. The structure of these technologies relies on the deep integration of advanced data-driven techniques which can ensure efcient energy generation, transmission, and distribution. After conducting thorough research for more than a decade, the concept of the smart grid (SG) has emerged, and its practice around the world paves the ways for efcient use of reliable energy technology. However, many developing features evoke keen interest and their improvements can be regarded as the next-generation smart grid (NGSG). Also, to deal with the non-linearity and uncertainty, the emergence of data-driven NGSG technology can become a great initiative to reduce the diverse impact of non-linearity. This paper exhibits the conceptual framework of NGSG by enabling some intelligent technical features to ensure its reliable operation, including intelligent control, agent-based energy conversion, edge computing for energy management, internet of things (IoT) enabled inverter, agent-oriented demand side management, etc. Also, a study on the development of data-driven NGSG is discussed to facilitate the use of emerging data-driven techniques (DDTs) for the sustainable operation of the SG. The prospects of DDTs in the NGSG and their adaptation challenges in real-time are also explored in this paper from various points of view including engineering, technology, et al. Finally, the trends of DDTs towards securing sustainable and clean energy evolution from the NGSG technology in order to keep the environment safe is also studied, while some major future issues are highlighted. This paper can ofer extended support for engineers and researchers in the context of data-driven technology and the SG.     

Sliding mode controller design via delay-dependent H∞ stabilization criterion for load frequency regulation

This work presents a control approach based on sliding-mode-control (SMC) to design robust H∞ state feedback controllers for load frequency regulation of delayed interconnected power system (IPS) with parametric uncertainties. Considering both state feedback control strategy and delayed feedback control strategy, two SMC laws are proposed. The proposed control laws are designed to improve the stability and disturbance rejection performance of delayed IPS, while stabilization criteria in the form of linear matrix inequality are derived by choosing a Lyapunov–Krasovskii functional. An artifcial time-delay is incorporated in the control law design of the delayed feedback control structure to enhance the controller performance. A numerical example is considered to study the control performance of the proposed controllers and simulation results are provided to observe the dynamic response of the IPS.     

A performance evaluation framework of public health distribution network for essential medicines: lessons from the select Indian states

The present work has been carried out to develop a performance evaluation framework of distribution network design in public health with specific reference to essential medicines based on six different types of public health distribution networks (PHDNs) prevalent across six Indian states. We evaluated the performance of PHDNs on the criteria of cost and service and also on the sub-criteria of cost and service by following the analytic hierarchy process. We utilized the pairwise comparison method in determining the relative importance of criteria and sub-criteria by seeking responses from several experts and subsequently evaluated the PHDNs on all sub-criteria in a 7-point Likert scale by seeking views from the same experts. Finally, we developed the “cost–service matrix,” in which cost and service have been depicted in the horizontal and vertical axes, respectively. We demonstrated the performance of six PHDNs in this matrix in terms of cost and service by plotting scores obtained by them on cost and service, respectively. The findings of the study provide rich insights to the policy planners of public health.     

A matching game framework for users clustering and resource allocation with wireless power transfer in a CR-NOMA network

This paper investigates the resource allocation in a massively deployed user cognitive radio enabled non-orthogonal multiple access (CR-NOMA) network considering the downlink scenario. The system performance deteriorates with the number of users who are experiencing similar channel characteristics from the base station (BS) in NOMA. To address this challenge, we propose a framework for maximizing the system throughput that is based on one-to-one matching game theory integrated with the machine learning technique. The proposed approach is decomposed to solve users clustering and power allocation subproblems. The selection of optimal cluster heads (CHs) and their associated cluster members is based on Gale-Shapley matching game theoretical model with the application of Hungarian method. The CHs can harvest energy from the BS and transfer their surplus power to the primary user (PU) through wireless power transfer. In return, they are allowed to access the licensed band for secondary transmission. The power allocation to the users intended for power conservation at CHs is formulated as a probabilistic constraint, which is then solved by employing the support vector machine (SVM) algorithm. The simulation results demonstrate the efficacy of our proposed schemes that enable the CHs to transfer the residual power while ensuring maximum system throughput. The effects of different parameters on the performance are also studied.     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

Energy Efficient Hardware Loop Based Optimization for CGRAs

Journal of Signal Processing Systems - Research interest and industry investment in edge computing solutions have increased dramatically in recent years. Consequent quest for balanced performance,...     

Secure video communication using firefly optimization and visual cryptography

In recent years, we face an increasing interest in protecting multimedia data and copyrights due to the high exchange of information. Attackers are trying to get confidential information from various sources, which brings the importance of securing the data. Many researchers implemented techniques to hide secret information to maintain the integrity and privacy of data. In order to protect confidential data, histogram-based reversible data hiding with other cryptographic algorithms are widely used. Therefore, in the proposed work, a robust method for securing digital video is suggested. We implemented histogram bit shifting based reversible data hiding by embedding the encrypted watermark in featured video frames. Histogram bit shifting is used for hiding highly secured watermarks so that security for the watermark symbol is also being achieved. The novelty of the work is that only based on the quality threshold a few unique frames are selected, which holds the encrypted watermark symbol. The optimal value for this threshold is obtained using the Firefly Algorithm. The proposed method is capable of hiding high-capacity data in the video signal. The experimental result shows the higher capacity and video quality compared to other reversible data hiding techniques. The recovered watermark provides better identity identification against various attacks. A high value of PSNR and a low value of BER and MSE is reported from the results.

     

Development and validation of a Re-Modified Work-Style Short Form Questionnaire for assessment of stress in medical practitioners working in Indian hospitals

Medical practitioners are unduly stressed, leading to ill health, loss of work efficiency, sometimes affecting decision-making capability. The present study was conducted with the aim to quantify the psychosocial factors that affect the medical practitioners working in Indian hospitals. This study constructed and validated Re-Modified Work-Style Short Form Questionnaire, an eight-item instrument based on work style of 108 medical practitioners comprising Indian physicians and surgeons. The re-modified tool had acceptable validity and internal consistency, which the modified one did not. Explorative factor analysis identified and labelled three factors: ‘Working through pain’, ‘Deadlines/pressure’ and ‘Self-imposed workload’. The findings of the study reveal that the mean total work style score exceeded the standardised limits ≥16, which suggests that the work style of medical practitioners working in Indian hospitals are at risk which may precipitate psychosocial stress. Factor weights was derived through Analytic Hierarchy Process to prioritise the relative importance of three potential work-style factors. The study may help to increase the preventive strategies to proactively reduce the effect of risk factors for the precipitation of stress, successfully leading to its attenuation.     

Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach

Sustainable development has become one of the leading global issues over the period of time. Currently, implementation of sustainability in supply chain has been continuously in center of attention due to introducing stringent legislations regarding environmental pollution by various governments and increasing stakeholders’ concerns toward social injustice. Unfortunately, literature is still scarce on studies considering all three dimensions (economical, environmental and social) of sustainability for the supply chain. An effective supply chain network design (SCND) is very important to implement sustainability in supply chain. This study proposes an uncertain SCND model that minimizes the total supply chain-oriented cost and determines the opening of plants, warehouses and flow of materials across the supply chain network by considering various carbon emissions and social factors. In this study, a new AHP and fuzzy TOPSIS-based methodology is proposed to transform qualitative social factors into quantitative social index, which is subsequently used in chance-constrained SCND model with an aim at reducing negative social impact. Further, the carbon emission of supply chain is estimated by considering a composite emission that consists of raw material, production, transportation and handling emissions. In the model, a carbon emission cap is imposed on total supply chain to reduce the carbon footprint of supply chain. To solve the proposed model, a code is developed in AMPL software using a nonlinear solver SNOPT. The applicability of the proposed model is illustrated with a numerical example. The sensitivity analysis examines the effects of reducing carbon footprint cap, negative social impacts and varying probability on the total cost of the supply chain. It is observed that a stricter carbon cap over supply chain network leads to opening of more plants across the supply chain. In addition, carbon footprint of supply chain is found to be decreased in certain extent with the reduction in negative social impacts from suppliers. The carbon footprint of the supply chain is found to be reduced with increasing certainty of material supply from the suppliers. The total supply chain cost is observed to be augmented with increasing probability.