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This study aims to assess the retail formats in India have evolved vastly over a relatively short period of seven to eight years. Human resource management practices in Organized retailing outlet with special reference to selected retailers in Coimbatore city. Retailers today are focused on drawing customers into the Stores to drive sales while at the same time reducing cost overheads. This present study aims to focus on beyond the impact of globalization and mergers and acquisitions, retail organizations continue to struggle with the recruitment of service-oriented employees. Keywords: Human Resource Management, Organized, retailing, Growth and retailers .

Color medical images hold noteworthy impact in clinical conclusion and treatment. Medical image segmentation reduces the uncertainty by providing detailed information about the shape, size, or location characteristics. However, traditional methods suffer from low accuracy, high complexity, and are less robust. To overcome these drawbacks, this paper proposes an efficient metaheuristic algorithm, exchange market algorithm (EMA) for multilevel thresholding (MLT) of distinct medical images. Optimal threshold is effectively obtained through the most promising objective functions such as Kapur, Otsu and minimum cross entropy (MCE) aided with EMA. The EMA involves exchange of shares among the investors in stable and unstable market situations to achieve profit. Exploration and exploitation are achieved by second and third groups of stable and unstable modes of EMA. Moreover, the execution time is reduced by the highly competent shareholders retaining their top rank without any changes in their shares. The efficacy of the proposed paper is evaluated on three distinct medical images at 4, 5, 6 and 7th threshold levels and compared with the recent algorithms such as Krill herd (KHA), Teaching-learning based optimization (TLBO) and Cuckoo search algorithm (CSA). Quantitative and qualitative validation by metrics such as computational time, Peak signal to noise ratio (PSNR), Structural similarity index (SSIM) and Wilcoxon rank sum test affirm that the EMA is superior to other algorithms. On the other hand, Otsu based EMA method is found to be more accurate and robust for improved clinical decision making and diagnosis.

Two hundred adult men between 36 and 55 years were selected for the assessment of their nutritional status. Information pertaining to socio economic status, anthropometric measurement, clinical profile and dietary pattern was collected using interview schedule. Energy costs of the activities were also collected. Information on the dietary nutrient intake was collected using 3-day dietary recall method. Anthropometric measurements namely height, weight, BMI and waist hip ratio were analyzed using standard procedures. Data was statistically analyzed. Results show that a greater percentage of the selected adult men were involved in moderate activity and belonged in middle income group. The educational qualification showed that 66% have completed school. The greater percentages of the selected subjects were from nuclear family. Most of the subjects were of normal height when compared with reference value. BMI revealed that forty nine percent were normal, 30% were overweight and 21% were obesity. Most of the selected subjects had WHR greater than 1. The food habits showed that majority of them were non vegetarians. Consumption of green leafy vegetables and fruits was less. On the contrary rice, wheat, red gram dhal were consumed daily. Most of the selected subjects mean nutrient intake was deficit when compared to RDA. The results of energy balance study showed that mean positive energy balance was 2098.2±90 kcal in the selected subjects. Nutrition education was given by power point, charts, pamphlets and a low energy snack was formulated and demonstrated used in the nutrition education programme. Results of paired t-test done shows that the nutrition education was effective (t = 3.84) and helped in improving the nutrition knowledge. The formulated product contains high amount of fibre. There is a need for educating these subjects on the right type and quantity of foods, higher intake of fibre rich foods, as well as the importance of regular physical activity to combat obesity.

In this paper, a new robust computational method that applies the geometrical theory of diffraction (GTD) in conjunction with the ray tracing (RT) technique is developed to evaluate the electromagnetic scattering pattern due to a plane wave represented as beam of parallel rays incident on a rough surface of quite arbitrary statistical parameters. The development of the proposed technique is explained in detail taking into consideration the generation of the geometrical model of the rough surface. The Fresnel reflection model is applied under the assumption of arbitrary electrical and optical properties of the rough surface material. Also the polarization of the plane wave primarily incident on the rough surface is taken into consideration. The algorithm developed in the present work accounts for multiple bounces of an incident ray and, hence, it can be considered arbitrary higher-order GTD-RT technique. The accuracy of the obtained results is verified through the comparison with the experimental measurements of the scattering pattern of a light beam incident on rough sheets with specific statistical properties. The numerical results of the present work are concerned with investigating the dependence of the scattering pattern on the surface roughness, refractive index, angle of incidence, and the resolution of the geometric model of the rough surface. Also, it is shown that, for limited resolution of the rough surface model, the accuracy of the calculated scattered field depends on the angle of incidence of the primary beam and the surface roughness.

The main objective of multi-area economic/environmental dispatch (MAEED) problems is the effective management of electrical energy generation by minimizing the total fuel cost and emissions of a multi-area power generation units, while satisfying various system and operating constraints. This paper bestows a new swarm intelligence approach, multi-objective squirrel search algorithm (MOSSA) to solve the MAEED problem. In the suggested approach, an exterior elitist vault system, crowding distance and fuzzy clustering principles are acquainted to procure a uniformly spaced Pareto optimal front curve. In addition, the MAEED problem is unraveled by squirrel search algorithm based weighted sum approach (SSA-WSA) with price penalty factors, artificial bee colony (ABC) and exchange market algorithm (EMA). The adequacy of the suggested strategy is approved on 40 generating units with single and multi-area power systems. The numeric results exhibit that the suggested MOSSA strategy accomplished much preferred trade-off solutions over the SSA-WSA, ABC, EMA and different strategies surfaced in the literature. The result transmuted evinces the desirability of MOSSA to solve the MAEED problem.

The essential goal of multi-area economic environmental dispatch (MAEED) is to determine the optimum power generation schedule of each unit and power transfer between the areas in order to minimize fuel costs and pollutant emissions, when the generation, power balance and tie-line limits are satisfied. This paper focuses on developing multi-objective squirrel search algorithm (MOSSA) to solve the MAEED problem, of which the goal is to simultaneously minimize the total fuel cost and emission considering valve point effects and multi-fuel options. The proposed MOSSA combines squirrel search algorithm along with Pareto-dominance theory to generate non-dominated solutions. It uses an external elitist depository mechanism with crowding distance sorting to preserve the distribution diversity of Pareto-optimal solutions as the evolution continues. In addition, a fuzzy decision maker is used to select the best compromised solution from the obtained Pareto frontiers. Furthermore, the MAEED problem is unraveled by squirrel search algorithm based weighted sum approach with price penalty factors, artificial bee colony and exchange market algorithm. Different case studies are performed on 10-unit with three-area system, 40-unit with four-area system and 140-unit real Korean power system considering valve point effects and multi-fuel options which testify the supremacy of the suggested approach. The comparisons with state-of-the-art approaches suggest that MOSSA can generate more competitive trade-off solutions for solving the MAEED problems.

Machine learning is an approach of artificial intelligence (AI) where the machine can automatically learn and improve its performance on experience. It is not explicitly programmed; the data is fed into the generic algorithm and it builds logic based on the data provided. Traditional algorithms have to define new rules or massive rules when the pattern varies or the number of patterns increases, which reduces the accuracy or efficiency of the algorithms. But the machine learning algorithms learn new input patterns capable of handling complex situations while maintaining accuracy and efficiency. Due to its effectual benefits, machine learning algorithms are used in various domains like healthcare, industries, travel, game development, social media services, robotics, and surveillance and information security. In this chapter, the application of machine learning technique in healthcare is discussed in detail.

Multilevel thresholding (MLT) is one of the most widely used methods in image segmentation. However, the exhaustive search method is computationally time consuming for selecting the optimal thresholds. Consequently, heuristic algorithms are extensively used to reduce the complexity of the MLT problem. In this paper, an efficient Exchange Market Algorithm (EMA) is proposed to segment images using minimum cross entropy thresholding method. In the EMA, a market risk variable is used to balance the exploration and exploitation capabilities of the algorithm. Moreover, the local search capability is strengthened by the search and absorbent operators of EMA. Meanwhile, the most competent shareholders of EMA retain their best rank without undergoing any changes in their shares. These help in reducing the computational time. The proposed EMA based MLT is tested on benchmark and brain images with different threshold levels. Additionally, EMA approach is compared with other well-known algorithms such as, genetic algorithm, particle swarm optimization, bacterial foraging algorithm, firefly algorithm, honey bee mating optimization and teaching–learning based optimization. The experimental results show that the proposed EMA approach provides better outcomes than other algorithms.

This paper proposes a computer-aided methodology for detecting and segmenting the tumor regions in ultrasound thyroid images using machine and deep learning algorithms. This proposed tumor detectio...

Copy move forgery (CMF) of digital images is the frequently adapted tampering by simply copying a region of the image and pasting it on to the same image using user-friendly image processing tools....

PurposeEconomic load dispatch (ELD) is one of the crucial optimization problems in power system planning and operation. The ELD problem with valve point loading (VPL) and multi-fuel options (MFO) is defined as a non-smooth and non-convex optimization problem with equality and inequality constraints, which obliges an efficient heuristic strategy to be addressed. The purpose of this study is to present a new and powerful heuristic optimization technique (HOT) named as squirrel search algorithm (SSA) to solve non-convex ELD problems of large-scale power plants.Design/methodology/approachThe suggested SSA approach is aimed to minimize the total fuel cost consumption of power plant considering their generation values as decision variables while satisfying the problem constraints. It confers a solution to the ELD issue by anchoring with foraging behavior of squirrels based on the dynamic jumping and gliding strategies. Furthermore, a heuristic approach and selection rules are used in SSA to handle the constraints appropriately.FindingsEmpirical results authenticate the superior performance of SSA technique by validating on four different large-scale systems. Comparing SSA with other HOTs, numerical results depict its proficiencies with high-qualitative solution and by its excellent computational efficiency to solve the ELD problems with non-smooth fuel cost function addressing the VPL and MFO. Moreover, the non-parametric tests prove the robustness and efficacy of the suggested SSA and demonstrate that it can be used as a competent optimizer for solving the real-world large-scale non-convex ELD problems.Practical implicationsThis study has compared various HOTs to determine optimal generation scheduling for large-scale ELD problems. Consequently, its comparative analysis will be beneficial to power engineers for accurate generation planning.Originality/valueTo the best of the authors’ knowledge, this manuscript is the first research work of using SSA approach for solving ELD problems. Consequently, the solution to this problem configures the key contribution of this paper.

This paper bestows a new swarm intelligence approach, Squirrel Search Algorithm (SSA) to solve Economic Load Dispatch (ELD) of the thermal unit by addressing the valve point loading effects and mul...

Five new multicomponent salts of perchloric acid with a series of substituted anilines and N-heterocyclic amines namely Diphenylaminium perchlorate (DPAPC) (1), 2, 5-dichloroanilinium perchlorate (25DAP) hydrate (2), 4-Methylanilinium perchlorate (4MAPC) (3), 4-diamino-6-methyl-1, 3, 5-triazin-1-ium hydrogen perchlorate (24DAMTHP) (4) and 8-hydroxyquinolinium hydrogen perchlorate (8HQP) (5) were prepared and structurally characterized. The entire complexes were subjected to FTIR and elemental analysis. A vast family of intermolecular contacts N-H…O, O-H…O, N-H…N and C-H…O were observed, which are key ingredient in the generation of privileged supramolecular self-assemblies appeared as one-dimensional chain, two-dimensional ladder and helix. Cambridge structural Database (CSD) analysis of 52 hits revealed the perchloric acid display higher propensity of ladder architectures. Molecular stability of the complexes were studied by quantum chemical calculations using DFT/B3LYP method with 6-31G(d,p) basis set. Further their relative charge distributions were identified using molecular electrostatic potential map. The use of Hirshfeld surfaces in combination with fingerprint plots was visualized in order to study the closer contacts within the molecule. The relative contribution of whole percentage of interactions associated is highlighted.

Wound dressings play a vital role in the wound healing process. Although a variety of wound dressings have been developed so far, most of them still have many drawbacks such as rigidity, non-porosity, low mechanical strength, an affinity to stick onto the injury surface and less antimicrobial activity. To overcome these issues, a novel type of porous three-dimensional (3D) film was fabricated using chitosan/carboxymethyl pullulan polyelectrolyte complex (PEC) loaded with 45S5 bioglass (CCMPBG) by the freeze-drying method for wound healing application. The developed films were analysed by FTIR, XRD, EDS and SEM to confirm their chemical nature, microstructure and surface morphologies. The CCMPBG films exhibited rough surface morphology and well-interconnected micropores with an average size range of 101–74 μm. Compared to the control chitosan/carboxymethyl pullulan (CCMP) film, the CCMPBG films showed an enhanced mechanical strength and controlled rate of swelling and biodegradation behaviours due to the interaction of polymer matrix and 45S5 bioglass (BG). Furthermore, CCMPBG films presented the improved biocompatibility, antimicrobial activity and wound closure ability because of the synergistic effects of chitosan, carboxymethyl pullulan (CMP) and BG. The results demonstrated that CCMPBG films can be an effective dressing material for wound therapy.