Intelligent Learning Algorithms for Active Vibration Control

YesThis correspondence presents an investigation into the comparative performance of an active vibration control (AVC) system using a number of intelligent learning algorithms. Recursive least square (RLS), evolutionary genetic algorithms (GAs), general regression neural network (GRNN), and adaptive neuro-fuzzy inference system (ANFIS) algorithms are proposed to develop the mechanisms of an AVC system. The controller is designed on the basis of optimal vibration suppression using a plant model. A simulation platform of a flexible beam system in transverse vibration using a finite difference method is considered to demonstrate the capabilities of the AVC system using RLS, GAs, GRNN, and ANFIS. The simulation model of the AVC system is implemented, tested, and its performance is assessed for the system identification models using the proposed algorithms. Finally, a comparative performance of the algorithms in implementing the model of the AVC system is presented and discussed through a set of experiments

The mediating role of corporate governance and corporate image on the CSR-FP link

This study advances research on CSR through investigating the CSR-firm financial performance (FP) link. It develops a model based on legitimacy and institutional theories and considers two important intervening variables – corporate governance and corporate image. The CSR practices are supposed to affect the corporate governance codes and principles in different contexts, especially in developing countries. Empirical results, based on a sample of 155 firms in a developing country, support the link between CSR and FP; however, the effect is indirect while corporate governance and corporate image fully mediate this link. The findings indicate that the CSR engagements help better governance practice and improve corporate image through establishing good internal controls and monitoring that ultimately enhance financial performance. The implications are valuable for academics, managers, and policy makers who are interested to measure the impact of intervening variables on the CSR-FP relationship

Intelligent Active Vibration Control for a Flexible Beam System

YesThis paper presents an investigation into the development of an intelligent active vibration control (AVC) system. Evolutionary Genetic algorithms (GAs) and Adaptive Neuro-Fuzzy Inference system (ANFIS) algorithms are used to develop mechanisms of an AVC system, where the controller is designed on the basis of optimal vibration suppression using the plant model. A simulation platform of a flexible beam system in transverse vibration using finite difference (FD) method is considered to demonstrate the capabilities of the AVC system using GAs and ANFIS. MATLAB GA tool box for GAs and Fuzzy Logic tool box for ANFIS function are used for AVC system design. The system is then implemented, tested and its performance assessed for GAs and ANFIS based design. Finally a comparative performance of the algorithm in implementing AVC system using GAs and ANFIS is presented and discussed through a set of experiments

Laboratory Investigation on the Behaviour of Improved Organic Soil of Khulna Region

The conventional foundation systems are not suitable for the massive structures in Khulna region i.e. South-west part of Bangladesh because an organic soil layer exists at a depth 10ft to 25ft from the existing ground surface. The existence of organic soil layer in the deposits results excessive settlement due to its high compressibility and low shear strength. To overcome the problem, soil improvement techniques are usually adopted depending upon the type of constructions. It is necessary to know the degree of improvement for the different improved grounds prior to the selection of ground improvement techniques. So a laboratory investigation was conducted to find out the effect of improvement techniques on reconstituted organic soil to obtain a guideline for selection, design and construction of suitable soil improvement method for this region. The laboratory investigation reveals that the compacted sand bed improves bearing capacity of organic ground significantly

Scheduling of tasks in multiprocessor system using hybrid genetic algorithms

This paper presents an investigation into the optimal scheduling of realtime tasks of a multiprocessor system using hybrid genetic algorithms (GAs). A comparative study of heuristic approaches such as `Earliest Deadline First (EDF)¿ and `Shortest Computation Time First (SCTF)¿ and genetic algorithm is explored and demonstrated. The results of the simulation study using MATLAB is presented and discussed. Finally, conclusions are drawn from the results obtained that genetic algorithm can be used for scheduling of real-time tasks to meet deadlines, in turn to obtain high processor utilization

Highly selective and sensitive macrocycle-based dinuclear foldamer for fluorometric and colorimetric sensing of citrate in water.

The selective detection of citrate anions is essential for various biological functions in living systems. A quantitative assessment of citrate is required for the diagnosis of various diseases in the human body; however, it is extremely challenging to develop efficient fluorescence and color-detecting molecular probes for sensing citrate in water. Herein, we report a macrocycle-based dinuclear foldamer (1) assembled with eosin Y (EY) that has been studied for anion binding by fluorescence and colorimetric techniques in water at neutral pH. Results from the fluorescence titrations reveal that the 1·EY ensemble strongly binds citrate anions, showing remarkable selectivity over a wide range of inorganic and carboxylate anions. The addition of citrate anions to the 1·EY adduct led to a large fluorescence enhancement, displaying a detectable color change under both visible and UV light in water up to 2 μmol. The biocompatibility of 1·EY as an intracellular carrier in a biological system was evaluated on primary human foreskin fibroblast (HF) cells, showing an excellent cell viability. The strong binding properties of the ensemble allow it to be used as a highly sensitive, detective probe for biologically relevant citrate anions in various applications

Impact of algorithm design in implementing real-time active control systems

This paper presents an investigation into the impact of algorithm design for real-time active control systems. An active vibration control (AVC) algorithm for flexible beam systems is employed to demonstrate the critical design impact for real-time control applications. The AVC algorithm is analyzed, designed in various forms and implemented to explore the impact. Finally, a comparative real-time computing performance of the algorithms is presented and discussed to demonstrate the merits of different design mechanisms through a set of experiments