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The Secretary of State in exercise of powers conferred by sections 138(1) and 180(3) of the Factories Act 1961 and now vested in him and of all other powers enabling him in that behalf, hereby makes the following Order:—

The problem of choosing the utmost useful features from hundreds of features from time-series user click data arises in online advertising toward fraudulent publisher's classification. Selecting feature subsets is a key issue in such classification tasks. Practically, the use of filter approaches is common; however, they neglect the correlations amid features. Conversely, wrapper approaches could not be applied due to their complexities. Moreover, in particular, existing feature selection methods could not handle such data, which is one of the major causes of instability of feature selection.

To overcome such issues, a majority voting-based hybrid feature selection method, namely feature distillation and accumulated selection (FDAS), is proposed to investigate the optimal subset of relevant features for analyzing the publisher's fraudulent conduct. FDAS works in two phases: (1) feature distillation, where significant features from standard filter and wrapper feature selection methods are obtained using majority voting; (2) accumulated selection, where we enumerated an accumulated evaluation of relevant feature subset to search for an optimal feature subset using effective machine learning (ML) models.

Empirical results prove enhanced classification performance with proposed features in average precision, recall, f1-score and AUC in publisher identification and classification.

The FDAS is evaluated on FDMA2012 user-click data and nine other benchmark datasets to gauge its generalizing characteristics, first, considering original features, second, with relevant feature subsets selected by feature selection (FS) methods, third, with optimal feature subset obtained by the proposed approach. ANOVA significance test is conducted to demonstrate significant differences between independent features.

The purpose of this paper is to investigate the impact of the foreign investment on the exit and sales of the domestic firms. Furthermore, it studies whether domestic firms undergo different influences by foreign firms according to the size of domestic firms.

Korean firm-level data for the period of 2006 through 2013 provided by Statistics Korea are used to study the impact of the foreign investment on the exit and sales of the domestic firms.

The result shows that foreign firms crowd out small firms from the market and take their shares in the domestic market. On the other hand, larger firms rather enjoy positive spillover effect from foreign firms, reducing its exit probability and increasing sales. It may be that large firms have enough competitiveness and ability to learn and apply the advanced technology of the foreign firms.

Despite the strong belief on the positive impacts of the foreign firms such as knowledge spillovers or job creation, there might be crowding-out or market-stealing effect from the presence of foreign firms. If the latter effect is larger than positive effect, the incentives provided by host country government to the multinational firms cannot be justified. In this regard, the question addressed in this paper is very important.

While most of previous papers have focused on the impacts of the foreign firms on productivity of the domestic firms, this paper deals with their impacts on the exit and sales of the domestic firms in order to examine more direct crowding-out and market-stealing effect of foreign firms.

The present and potential applications of screen‐printing thick film technology to the field of chemical sensing are briefly reviewed in the first part of the paper. The second part is devoted to the search for new routes to selectivity for basically non‐selective gas sensors.

THE first part of Professor Duncan Dowson's paper (March/April issue) dwelt on late 19th century development of machinery outstripping the performance of available lubricants. Contemporary lubricant research, and personalities involved, where described, leading to the concept of fluid‐film lubrication, documented by Professor Osborne Reynolds' paper read to the Royal Society in 1886.

Corporate social responsibility (CSR) rating agencies have arisen with the aim of providing external and reliable information about business behaviour. The purpose of this paper is to present a multi-criteria methodology for integrating CSR valuations with the financial performance of companies in a unique measure of global sustainability performance.

The authors present a hybrid TOPSIS methodology on transformed scores of both the CSR valuations and the financial ratios. The “attribute-specific evaluation” approach into Multi-attribute Prospect Theory (PT) has been applied and the Design of Experiments (DoE) is used with the TOPSIS value of the firm as the response variable.

The proposal has been applied to 118 companies evaluated by Vigeo and Covalence CSR agencies. The authors also have considered five financial ratios of the companies in order to assess their financial performance. Consistent aggregation for firms has been achieved. Relationships between the different rankings, both those of Vigeo and Covalence and the ones constructed in this research, have been analysed. All top 10 Global sustainable firms rank among the top 10 positions in at least one of the remaining rankings. The results show that Vigeo and Covalence provide different information about the CSR behaviour of the companies.

Another interesting question is to study the discrepancies between Vigeo and Covalence, for example, in which areas there is the greatest divergence between the two agencies and what could be the reasons for this.

The results of this research could be of interest for both investors who want a global picture of companies in their selection process and stakeholders concerned with CSR issues who want to take advantage of different CSR ratings.

The application of PT softens the compensatory behaviour of the classical TOPSIS that may prove unsuitable for social evaluation. The DoE allows the aggregation of the weight sets from various decision markers. The combined methodology facilitates the scoring of new firms and the rank reversal problem can be mitigated with this methodology.

This paper aims to propose an innovative building information modelling (BIM)-based framework for multi-objective and dynamic temporary construction site layout design (SLD), which uses a hybrid approach of systematic layout planning (SLP) and mathematical modelling.

The hybrid approach, which follows a step-by-step process for site layout planning, is designed to facilitate both qualitative and quantitative data collection and processing. BIM platform is usedto facilitate the determination of the required quantitative data, while the qualitative data are generated through knowledge-based rules.

The multi-objective layout model represents two important aspects: layout cost and adjacency score. The result shows that the model meets construction managers’ requirements in not only saving cost but also assuring the preferences of temporary facility relationships. This implies that the integration of SLP and mathematical layout modelling is an appropriate approach to deliver practical multi-objective SLD solutions.

The proposed framework is expected to serve as a solution, for practical application, which takes the advantage of technologies in data collection and processing. Besides, this paper demonstrates, by using numerical experimentation and applying Microsoft Excel Solver for site layout optimisation, how to reduce the complexity in mathematical programming for construction managers.

The original contribution of this paper is the attempt of developing a framework in which all data used for the site layout modelling are collected and processed using a systematic approach, instead of being predetermined, as in many previous studies.

Total quality management (TQM) has long been viewed as a strategy to attain business excellence. However, it is relatively a new concept in the context of emerging economies. Particularly, this is far beyond the reality in the context of African countries, in general. The purpose of this paper is to study the current state of TQM implementation in the manufacturing industry of Ethiopia (MIE). The study also focuses on several comparisons, between large and medium companies, and ISO and non-ISO companies with regard to the adoption of TQM practices.

The study draws on top- and middle-level managers from sample companies. Data were collected using a structured survey questionnaire. After testing scale reliability and validity, descriptive and factor analysis were used for the data analysis.

The findings, in general, indicated that Ethiopian manufacturers have implemented TQM at a moderate level (grand mean value of 2.86 on 0–5 scale). It is revealed that ISO companies are significantly adopted TQM practices than non-ISO companies, whereas no difference was found between large and medium companies.

Given the importance of understanding TQM and paucity of research on the topic in Ethiopia, the study provides practical insights and groundwork that can guide practitioners to understand the drivers of TQM in the region. Particularly, the study is useful to plan corrective actions on practices that are likely to obstruct TQM implementation in the MIE. Moreover, the study adds to the empirical literature that may yield important insights on TQM for under-researched emerging economies, particularly for the eastern part of Africa, where nations share similar cross-cultural norms, economic, social and ethnic settings.

The purpose of this paper is to study and develop supply chain structure of traditional Indian agri-fresh food supply chain (AFSC). This paper proposes a mathematical model to design a traditional Indian AFSC to minimize total distribution cost and post-harvest losses in the chain.

This paper formulates two mathematical models to structure and represent the flow of products in the existing chain. First, a three-echelon, multi-period, multi-product, mixed-integer linear programming (MILP) model is formulated to minimize the total distribution cost incurred in the chain. Further, the developed formulation is extended by considering the perishability of products in the second model.

A real case study problem of Mandsaur district (India) is solved in LINGO 17.0 package to check the validity of the formulated models. The perishable (second) model of AFSC reports better results in terms of costs and post-harvest losses minimization. The results revealed that 92% of the total distribution cost incurred in the transportation of products from farmers to the hubs.

This paper includes implications for redesigning an existing supply chain network by incorporating an appropriate transportation strategy from farmers to hubs to minimize transportation inefficiency and enhance the profitability of farmers.

The formulated AFSC model would help managers and policymakers to identify optimal locations for hubs where required infrastructure would be developed.

According to the author's best knowledge, this paper is the first to design traditional Indian AFSC by considering the perishability of products.

The paper aims to improve upon the performance of a squeeze film formed by a magnetic fluid between longitudinally rough conical plates.

The objectives are achieved by mathematically modeling a magnetic fluid‐based squeeze film between longitudinally rough conical plates. The roughness of the bearing surface is modeled by a stochastic random variable with non‐zero mean, variance and skewness. The standard approach is to solve associated Reynold's equation which is stochastically averaged with respect to the random roughness parameter. The scope of this paper is the industrial applications with regard to enhanced performance of the bearing system.

The findings indicate that the performance of the bearing gets enhanced due to negatively skewed roughness. It is also noticed that the standard deviation increases the load carrying capacity which is unlike the case of transverse surface roughness. Further, this paper suggests that there exist considerable scopes for enhancing the performance of the longitudinally rough bearing system by choosing a suitable combination of the magnetization parameter and the semi‐vertical angle of the cone.

From the industry point of view, this investigation will be certainly useful for improving the performance of a magnetic fluid‐based squeeze film between longitudinally rough conical plates.

The paper presents the improved performance of a squeeze film formed by a magnetic fluid between longitudinally rough conical plates and thereby extending the life period of the bearing system.