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The purpose of this study is to develop an optimization method for charging plans with the implementation of time-of-day (TOD) electricity tariff, to reduce electricity bill.

Two optimization models for charging plans respectively with fixed and stochastic trip travel times are developed, to minimize the electricity costs of daily operation of an electric bus. The charging time is taken as the optimization variable. The TOD electricity tariff is considered, and the energy consumption model is developed based on real operation data. An optimal charging plan provides charging times at bus idle times in operation hours during the whole day (charging time is 0 if the bus is not get charged at idle time) which ensure the regular operation of every trip served by this bus.

The electricity costs of the bus route can be reduced by applying the optimal charging plans.

This paper produces a viable option for transit agencies to reduce their operation costs.

This paper proposes an approach to identify categorical influencers (i.e. influencers is the person who is active in the targeted categories) in social media channels. Categorical influencers are important for media marketing but to automatically detect them remains a challenge.

We deployed the emerging deep learning approaches. Precisely, we used word embedding to encode semantic information of words occurring in the common microtext of social media and used variational autoencoder (VAE) to approximate the topic modeling process, through which the active categories of influencers are automatically detected. We developed a system known as Categorical Influencer Detection (CID) to realize those ideas.

The approach of using VAE to simulate the Latent Dirichlet Allocation (LDA) process can effectively handle the task of topic modeling on the vast dataset of microtext on social media channels.

This work has two major contributions. The first one is the detection of topics on microtexts using deep learning approach. The second is the identification of categorical influencers in social media.

This work can help brands to do digital marketing on social media effectively by approaching appropriate influencers. A real case study is given to illustrate it.

In this paper, we discuss an approach to automatically identify the active categories of influencers by performing topic detection from the microtext related to the influencers in social media channels. To do so, we use deep learning to approximate the topic modeling process of the conventional approaches (such as LDA).

This paper seeks to find out which factors influence the willingness of professionals to contribute to a certification process and to understand the rationale behind this willingness.

Based on literature, prerequisites are formulated for the willingness of professionals to contribute to certification. These are compared with the results of a study among lecturers at Universities of Applied Sciences in The Netherlands and Flanders about their willingness to contribute to accreditation of their schools. This study combines survey and Delphi research.

Professionals agree on the added value of certification systems. They are willing to contribute to the certification process, provided that a set of conditions is fulfilled.

The case focuses on large organisations for which certification is obligatory. The findings may not apply in small or medium‐sized organisations or if the main driver for certification is internal improvement. Further research is needed to verify the generalisation of the results to other sectors and countries.

Research has shown that it is difficult to motivate professionals to contribute to certification. Little research has been done on the reasons why. The paper provides more insight into the difficulties that organizations face to commit their professionals to become involved in certification and turns these into requirements to be fulfilled to achieve commitment. These are relevant for organisations, which need the support of their professional employees to achieve management system certification.

This study aims to analyze the efficient market hypothesis (EMH) of cryptocurrencies on multiple platforms by observing whether there is a discrepancy in the levels of efficiency between different exchanges. Additionally, EMH is tested in a multivariate way: whether the prices of the same cryptocurrencies traded on different exchanges are temporally related to each other. ADF and KPSS tests, whereas the vector autoregression model of order p – VAR(p) – for multivariate system.

Both Bitcoin and Ethereum show efficiency in the weak form on the main platforms in each market alone. However, when estimating a VAR(p) between prices among exchanges, there was evidence of Granger causality between cryptocurrencies in all exchanges, suggesting that EMH is not adequate due to cross information.

It is essential to assess the cryptocurrency market in a multivariate way, not only to favor its maturation process, but also to promote a broad understanding of its inherent risks. Thus, it will be possible to develop financial products that are actively managed in a more sophisticated cryptocurrency market.

There is a possibility of performing arbitrage on different exchanges and market assets through cross-exchanges. Thus, emphasizing the need for regulation of exchanges in the digital asset market, as an eventual price manipulation on a single platform can impact others, which generates various distortions.

This study is the first to find evidence of cross-information for the same (and other) cryptocurrencies among different exchanges.

This article reviews the first volume of the Journal of Children's Services. In doing so, it discusses broader directions and challenges in research, policy and practice. The article focuses on discussion about outcomes, the ‘idea’ of children's services and the impact of interventions on children's health and development. It welcomes reflections on different approaches to outcome measurement, analyses of the practicalities of implementing policy reforms and rigorous evaluations of the impact of Early Years, parenting and other programmes. At the same time, it suggests specific areas in which more work would be valuable, including: socio‐political commentary on policy developments; methods of and results from need analyses; empirical research on inter‐agency initiatives; how to improve the processes and structures that underpin good outcomes; transitions; and understanding ‘what works’ in research dissemination and utilisation. The value of international perspectives (including intra‐UK comparisons) is stressed. Forthcoming special editions on randomised controlled trials (RCTs) (2007) and anti‐social behaviour by young people (2008) will help to address other points raised.

The purpose of this paper is to present an analytical study on an unsteady magnetohydrodynamic (MHD) boundary layer flow of a rotating viscoelastic fluid over an infinite vertical porous plate embedded in a uniform porous medium with oscillating free-stream taking Hall and ion-slip currents into account. The unsteady MHD flow in the rotating fluid system is generated due to the buoyancy forces arising from temperature and concentration differences in the field of gravity and oscillatory movement of the free-stream.

The resulting partial differential equations governing the fluid motion are solved analytically using the regular perturbation method by assuming a very small viscoelastic parameter. In order to note the influences of various system parameters and to discuss the important flow features, the numerical results for fluid velocity, temperature and species concentration are computed and depicted graphically vs boundary layer parameter whereas skin friction, Nusselt number and Sherwood number at the plate are computed and presented in tabular form.

An interesting observation is recorded that there occurs a reversal flow in the secondary flow direction due to the movement of the free stream. It is also noted that a decrease in the suction parameter gives a rise in momentum, thermal and concentration boundary layer thicknesses.

Very little research work is reported in the literature on non-Newtonian fluid dynamics where unsteady flow in the system arises due to time-dependent movement of the plate. The motive of the present analytical study is to analyse the influences of Hall and ion-slip currents on unsteady MHD natural convection flow of a rotating viscoelastic fluid (non-Newtonian fluid) over an infinite vertical porous plate embedded in a uniform porous medium with oscillating free-stream.

In the present investigation, hydromagnetic boundary layer flow of Walters’-B fluid over a vertical porous surface implanted in a porous material under the action of a strong external applied magnetic field and rotation is presented. In several industrial applications, the external applied magnetic field is strong enough to produce Hall and ion-slip currents. Thus, the influence of Hall and ion-slip currents is also considered in this analysis. The flow through configuration is generated because of time varying motion of the free-stream and buoyancy action.

Regular perturbation scheme is used to obtain the solution of the system of coupled partial differential equations representing the mathematical model of the problem. Numerical computation has been performed to notice the change in flow behavior and the numerical results for velocity field, temperature field, species concentration, skin friction, rate of heat and mass transfer are presented through graphs and tables.

An important fact noticed that the exponential time varying motion of the free-stream induces reverse flow in the direction perpendicular to the main flow. Rising values of the strength of the applied magnetic field give increment in the fluid velocity in the neighbourhood of the vertical surface, this may cause because of the exponential motion of the free-stream. The behaviour of the Darcian drag force is similar as magnetic field on fluid flow.

In literature, very less research works are available on Walters’-B fluid where unsteadiness in the system occurs because of time varying motion of the free-stream. In this paper, the authors have made an attempt to study the action of Hall and ion-slip currents, rotation and external applied magnetic field on hydromagnetic boundary layer flow of Walters’-B fluid over a vertical surface implanted in a porous material.

Diabetic retinopathy (DR) is a central root of blindness all over the world. Though DR is tough to diagnose in starting stages, and the detection procedure might be time-consuming even for qualified experts. Nowadays, intelligent disease detection techniques are extremely acceptable for progress analysis and recognition of various diseases. Therefore, a computer-aided diagnosis scheme based on intelligent learning approaches is intended to propose for diagnosing DR effectively using a benchmark dataset.

The proposed DR diagnostic procedure involves four main steps: (1) image pre-processing, (2) blood vessel segmentation, (3) feature extraction, and (4) classification. Initially, the retinal fundus image is taken for pre-processing with the help of Contrast Limited Adaptive Histogram Equalization (CLAHE) and average filter. In the next step, the blood vessel segmentation is carried out using a segmentation process with optimized gray-level thresholding. Once the blood vessels are extracted, feature extraction is done, using Local Binary Pattern (LBP), Texture Energy Measurement (TEM based on Laws of Texture Energy), and two entropy computations – Shanon's entropy, and Kapur's entropy. These collected features are subjected to a classifier called Neural Network (NN) with an optimized training algorithm. Both the gray-level thresholding and NN is enhanced by the Modified Levy Updated-Dragonfly Algorithm (MLU-DA), which operates to maximize the segmentation accuracy and to reduce the error difference between the predicted and actual outcomes of the NN. Finally, this classification error can correctly prove the efficiency of the proposed DR detection model.

The overall accuracy of the proposed MLU-DA was 16.6% superior to conventional classifiers, and the precision of the developed MLU-DA was 22% better than LM-NN, 16.6% better than PSO-NN, GWO-NN, and DA-NN. Finally, it is concluded that the implemented MLU-DA outperformed state-of-the-art algorithms in detecting DR.

This paper adopts the latest optimization algorithm called MLU-DA-Neural Network with optimal gray-level thresholding for detecting diabetic retinopathy disease. This is the first work utilizes MLU-DA-based Neural Network for computer-aided Diabetic Retinopathy diagnosis.

When induction motors are considered, there is no specific cost model for net savings per year due to condition-based maintenance (CBM) covering various parameters such as downtime, energy, quality, etc. The purpose of this paper is to develop a cost model for the financial viability of the implementation of CBM for induction motors.

A literature review has been carried out to identify the existing failure modes of motor, available condition monitoring techniques, the usefulness of CBM and different maintenance models available. Then, a cost model considering all parameters has been proposed.

A cost model has been proposed for the maintenance of induction motors. Method for the economic evaluation of the model has also been suggested in the paper. The application of the model has been illustrated through a case study of a steel plant, which suggests that investment in the condition monitoring of induction motors increases the net profit of the organization.

The proposed model is specifically designed for induction motors. All the motors under consideration are assumed to be of the same specifications, and fault in any motor is supposed to have the same effect on quality, cost, criticality, etc., of the operation and end product.

This paper will help the maintenance manager in decision making when maintenance action has to be carried out for a given motor under CBM for the better utilization of the equipment and resources. This paper also shows how to compute ROI on CBM investment.

The paper provides a cost model for the economic evaluation of implementing CBM for induction motors which will be useful to researchers and maintenance managers in effective decision making and maintenance planning. The methodology and the cost models are the original contribution of the authors.

The present study aims to focus on the possibility of developing new eco-friendly azo dyes with good colouristic application properties, exhibiting biological and pharmacological activities.

Coupling of 4-hydroxycoumarin with a variety of aromatic diazonium salts of 2-aminothiazole, 2-aminobenzothiazole, 4-aminoantipyrine, 4-aminoacetophenone, adenine sulphate, a-naphthylamine and sulphadimidine to produce novel azo dyes. The compounds were fully characterised using spectroscopic and analytical methods. All of the compounds were tested for their antimicrobial, anticancer and antioxidant activities. The prepared dyestuffs were dyed on polyester fabrics and subsequently their dyeing properties, light, washing, perspiration, rubbing and sublimation fastness were determined.

The spectroscopic data of the synthesised compounds have provided decisive evidence that such compounds exist in the solid state as the azo-dike to form C and in solution in equilibrium tautomer forms A, B and D. The prepared dyestuffs are suitable for either heat transfer printing or traditional printing on polyester and nylon 6 fabrics. The prints obtained from the dyes possess high colour strength, as well as good overall fastness properties. Also the synthesised compounds exhibit good biological and pharmacology activity.

Synthesis of these seven azo dyes for textile dyeing had never been reported previously.

The dyestuffs derived from 4-hydroxycoumarin are reasonable azo disperse dyestuffs giving good all round fastness properties on polyester fabrics.

Production of less expensive and new eco-friendly dyes exhibit antimicrobial and anticancer activity.

It provided a potentially simple way to synthesize novel coumarin azo-dyes exhibit good biological and pharmacology activity and also exhibit good overall fastness properties.