An evolutionary lion optimization algorithm‐based image compression technique for biomedical applications

Recently, medical image compression becomes essential to effectively handle large amounts of medical data for storage and communication purposes. Vector quantization (VQ) is a popular image compression technique, and the commonly used VQ model is Linde–Buzo–Gray (LBG) that constructs a local optimal codebook to compress images. The codebook construction was considered as an optimization problem, and a bioinspired algorithm was employed to solve it. This article proposed a VQ codebook construction approach called the L2‐LBG method utilizing the Lion optimization algorithm (LOA) and Lempel Ziv Markov chain Algorithm (LZMA). Once LOA constructed the codebook, LZMA was applied to compress the index table and further increase the compression performance of the LOA. A set of experimentation has been carried out using the benchmark medical images, and a comparative analysis was conducted with Cuckoo Search‐based LBG (CS‐LBG), Firefly‐based LBG (FF‐LBG) and JPEG2000. The compression efficiency of the presented model was validated in terms of compression ratio (CR), compression factor (CF), bit rate, and peak signal to noise ratio (PSNR). The proposed L2‐LBG method obtained a higher CR of 0.3425375 and PSNR value of 52.62459 compared to CS‐LBG, FA‐LBG, and JPEG2000 methods. The experimental values revealed that the L2‐LBG process yielded effective compression performance with a better‐quality reconstructed image.     

Finite element prediction of material removal rate due to electro-chemical spark machining

Electro-chemical spark machining (ECSM) is an innovative hybrid machining process, which combines the features of the electro-chemical machining (ECM) and electrodischarge machining (EDM). Unlike ECM and EDM, ECSM is capable of machining electrically non-conducting materials. This paper attempts to develop a thermal model for the calculation of material removal rate (MRR) during ECSM. First, temperature distribution within zone of influence of single spark is obtained with the application of finite element method (FEM). The nodal temperatures are further post processed for estimating MRR. The developed FEM based thermal model is found to be in the range of accuracy with the experimental results. Further the parametric studies are carried out for different parameters like electrolyte concentration, duty factor and energy partition. The increase in MRR is found to increase with increase in electrolyte concentration due to ECSM of soda lime glass workpiece material. Also, the change in the value of MRR for soda lime glass with concentration is found to be more than that of alumina. MRR is found to increase with increase in duty factor and energy partition for both soda lime glass and alumina workpiece material.     

An Energy-efficient Switching Scheme with Reduced Switching Transients for a Wind-driven Induction Generator

This article presents a scheme for improving the power output of grid-connected induction generator commonly used in wind energy conversion systems. Generally, the stator of the induction generator is connected in a star with a line voltage of √3 times the rated winding voltage to reduce the line current and, hence, conductor size. To extend the generating operation over a wider speed range, delta-star switchable stator windings are also in vogue. In such cases, the stator is star connected in the lower speed range and switched to a delta connection above a threshold speed. In this study, a new switching scheme is proposed wherein the stator coils are always connected in a star, while the stator is connected to different voltages in low- and high-speed conditions. At low wind speeds, nominal winding voltage is applied to the stator, whereas at higher speeds, the stator applied voltage is √3 times higher than the rated winding voltage. The efficacy of the scheme is demonstrated experimentally with a suitable microcontroller-based switching arrangement. Typical results indicate an increase in output with reduced switching transients. A case study on a 3-Φ, 50-kW induction generator is presented to emphasize the performance improvement with the proposed scheme.     

Hydrous iron oxide for removal of inorganic contaminants in simulated stormwater: A batch sorption kinetics study

Urban stormwater runoff, which consists of inorganic and organic contaminants, is a major source of pollutants to receiving waters and therefore they need to be removed. Simultaneous removal of contaminants, Cd²⁺, Cu²⁺, Ni²⁺, Zn²⁺ (heavy metal cations), and SeO₄²⁻ (oxyanion) from a simulated stormwater by a hydrous ferric oxide (HFO) was studied in batch and column sorption experiments. In the batch experiment the rate of sorption of the ions was rapid at the beginning and reached equilibrium in approximately 300 min. The amounts of ions sorbed were proportionate to the respective initial concentration of the ions added to the HFO. Cluster analysis showed that all heavy metals had similar sorption behavior, whereas Se had a distinctly different sorption process. Of the three different kinetic models tested the pseudo-first order kinetic model fitted the data the best. The column experimental results beyond 180 min were consistent with those of the batch experiment that the removal efficiencies of the ions were in proportion to the ion concentration in the feed. Below 180 min, Cu appeared to be preferentially removed than Zn.     

A tandem queue with general bulk service and servers' “vacation”

This paper analyses two queueing models consisting of two units I and II connected in series, separated by a finite buffer of size N. In both models, unit I has only one exponential server capable of serving customers one at a time and unit II consist of c parallel exponential servers, each of them serving customers in groups according to general bulk service rules. When the queue length in front of unit II is less than the minimum of batch size, the free servers take a vacation. On return from vacation, if the queue length is less than the minimum, they leave for another vacation in the first model, whereas in the second model they wait in the system until they get the minimum number of customers and then start servicing. The steady-state probability vector of the number of customers waiting and receiving service in unit I and waiting in the buffer is obtained for both the models, using the modified matrix geometric method. Numerical results are also presented.     

Velocity Distributions in Spatially Varied Flow with Increasing Discharge

The experimental study presented in this paper explores the distribution of the mean velocities for a channel receiving spatially varied (SV) inflow from directly above the centerline of the channel via sets of nozzles. The velocity components u, v, and w have been measured using a laser Doppler velocimeter. Initially the validity of the law of the wall in the channel receiving SV inflow was investigated. It was found that the measured velocity profile within the inertial sublayer region near the channel bed falls below the line representing the log law. Further, if the SV inflow enters at the center of the channel, the degree that the data depart from the log law increases from the sidewall toward the center of the channel. The structures of the velocity distributions are also presented in detail. The results include both near field, that is the area close to where the flow enters the channel, and far field measurements. It was found that the influence of the SV inflow on velocity profiles is largely contained within the SV inflow zone and that the influence within this zone reduces in the downstream direction. At any one section within this zone the influence reduces from the center of the channel toward the sidewall. In addition, some features of the secondary flow established by the SV inflow are described.     

Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review

Money laundering has been affecting the global economy for many years. Large sums of money are laundered every year, posing a threat to the global economy and its security. Money laundering encompasses illegal activities that are used to make illegally acquired funds appear legal and legitimate. This paper aims to provide a comprehensive survey of machine learning algorithms and methods applied to detect suspicious transactions. In particular, solutions of anti-money laundering typologies, link analysis, behavioural modelling, risk scoring, anomaly detection, and geographic capability have been identified and analysed. Key steps of data preparation, data transformation, and data analytics techniques have been discussed; existing machine learning algorithms and methods described in the literature have been categorised, summarised, and compared. Finally, what techniques were lacking or under-addressed in the existing research has been elaborated with the purpose of pinpointing future research directions.     

Scaling group transformation for MHD boundary-layer flow of a nanofluid past a vertical stretching surface in the presence of suction/injection

The problem of laminar fluid flow which results from the stretching of a vertical surface with variable stream conditions in a nanofluid has been investigated numerically. The model used for the nanofluid incorporates the effects of Brownian motion and thermophoresis in the presence of magnetic field. The symmetry groups admitted by the corresponding boundary value problem are obtained by using a special form of Lie group transformations viz. scaling group of transformations. An exact solution is obtained for translation symmetry and numerical solutions for scaling symmetry. This solution depends on a Lewis number, magnetic field, Brownian motion parameter and thermophoretic parameter. The conclusion is drawn that the flow field and temperature and nanoparticle volume fraction profiles are significantly influenced by these parameters.     

Method for fabricating the compact layer in dye-sensitized solar cells by titanium sputter deposition and acid-treatments

Dye-sensitized solar cells (DSCs) have been put forward as a potential low-cost alternative to the widely used silicon solar cells, which are subject to cost limitations. However, some problems need to be solved in order to enhance the efficiency of DSCs. In particular, the electron recombination occurred by the contact between the transparent conductive oxide (TCO) and a redox electrolyte is one of the main limiting factors of efficiency. Accordingly, a compact layer plays an important role in realizing highly efficient DSCs because it improves the adhesion of the TiO₂ to the TCO and provides a larger contact area and more effective electron transfer by preventing electron recombination. In this work, the fabrication of a TiO₂ compact layer using Ti sputter deposition and acid-treatment was investigated rather than the conventional method, which uses a TiCl₄ aqueous solution. The acid-treatment of the sputtered Ti film actively oxidized the Ti particles. As a result, such a cell exhibited an additional 1.3% in total efficiency compared to the standard DSC without a compact layer. These improvements are not inferior to those obtained by the conventional fabrication method using a TiCl₄ aqueous solution.