Prediction of mechanical property of steel strips using multivariate adaptive regression splines

In recent times, the problem of prediction of properties of a steel strip has attracted enormous attention from different communities such as statistics, data mining, soft computing, and engineering. This is due to the prospective benefits of reduction in testing and inventory cost, increase in yield, and improvement in delivery compliance. The complexity of the problem arises due to its dependency on the chemical composition of the steel, and a number of processing parameters. To predict the mechanical properties of the strip (yield strength, ultimate tensile strength, and Elongation), a model based on multivariate adaptive regression spline has been developed. It is found that the prediction agrees well with the actual measured data.     

M-estimators of some GARCH-type models; computation and application

In this paper, we consider robust M-estimation of time series models with both symmetric and asymmetric forms of heteroscedasticity related to the GARCH and GJR models. The class of estimators includes least absolute deviation (LAD), Huber’s, Cauchy and B-estimator as well as the well-known quasi maximum likelihood estimator (QMLE). Extensive simulations are used to check the relative performance of these estimators in both models and the weighted resampling methods are used to approximate the sampling distribution of M-estimators. Our study indicates that there are estimators that can perform better than QMLE and even outperform robust estimator such as LAD when the error distribution is heavy-tailed. These estimators are also applied to real data sets.     

Accountability and value for money: a theoretical framework for the relationship in public–private partnerships

There is an implicit assumption in the UK Treasury’s publications on public-private partnerships (PPP)—also more commonly known in the United Kingdom as private finance initiative (PFI)—that accountability and value for money (VFM) are related concepts. While recent academic studies on PPP/PFI (from now on as PFI) have focused on VFM, there is a notable absence of studies exploring the ‘presumed’ relationships between accountability and VFM. Drawing on Dubnick’s (Dubnick and Romzek in American public administration, politics and the management of expectations. Macmillan, New York, 1991, Research in public administration. JAI, Greenwich, 1993; Dubnick in Public service ethics and the cultures of blame, 1996, Public sector ethics: finding and implementing values. Routledge, London, 1998, Int J Org Theory Behav 6(3):405–441, 2003, Public Perform Manage Rev 28(3):376–417, 2005; Dubnick and Justice in But can you trust them to be ethical, 2002) framework for accountability and PFI literature, we develop a research framework for exploring potential relationships between accountability and VFM in PFI projects by proposing alternative accountability cultures, processes and mechanisms for PFI. The PFI accountability model is then exposed to four criteria—warrantability, tractability, measurability and feasibility. Our preliminary interviews provide us guidance in identifying some of the cultures, processes and mechanisms indicated in our model which should enable future researchers to test not only the UK Government’s claimed relationships between accountability and VFM using more specific PFI empirical data, but also a potential relationship between accountability and performance in general.     

A study of subjective visual disturbances in jewellery manufacturing

Subjective Visual Disturbances are silent adversaries that appear over a period of continued exposure and arise when the visual demands of the tasks exceed the visual abilities of the user. Jewellery manufacturing activity involves precision designs, setting the metal and stones, polishing and filing which requires higher visual demand. Therefore, it is expected that the jewellery manufacturing workers may experience subjective visual disturbances. This study was taken up with the following objectives 1) To study the presence of subjective visual disturbances among jewellery manufacturing workers and compare the same with VDT operators 2) To study the effect of work exposures on subjective visual disturbances and 3) to ascertain whether subjective visual disturbances have any permanent vision related problems. The study was carried out on jewellery manufacturing workers, VDT operators and on graduate students. The symptoms of subjective visual disturbances were identified using a questionnaire developed by Sheedy (2003). Viewing distances were measured and visual angles were calculated. The eye check--ups were also carried out. The subjective visual disturbances were higher in jewellery manufacturing workers. The findings suggest that work exposure has an impact on the causation of subjective visual disturbances. No pathological conditions of the eyes were observed.     

Progressive Variance Control Charts for Monitoring Process Dispersion

In a process, the deviation from location or scale parameters affects the quality of the process and waste resources. So it is essential to monitor such processes for possible changes due to any assignable causes. Control charts are the most famous tool used to meet this intention. It is useless to monitor process location until the assurance that process dispersion is in-control. This study proposes some new two-sided memory control charts named as progressive variance (PV) control charts which are based on sample variance to monitor changes in process dispersion assuming normality of quality characteristic to be monitored. Simulation studies are made, and an example is discussed to evaluate the performance of the proposed charts. The comparison of the proposed chart is made with exponentially weighted moving average- and cumulative sum-type charts for process dispersion. The study shows that performance of the proposed charts are uniformly better than its competitors for detecting positive shifts while for detecting negative shift in the variance their performance is better for small shifts and reasonably good for moderated shifts.     

Description and Propagation of Uncertainty in Input Parameters in Environmental Fate Models

Today, chemical risk and safety assessments rely heavily on the estimation of environmental fate by models. The key compound‐related properties in such models describe partitioning and reactivity. Uncertainty in determining these properties can be separated into random and systematic (incompleteness) components, requiring different types of representation. Here, we evaluate two approaches that are suitable to treat also systematic errors, fuzzy arithmetic, and probability bounds analysis. When a best estimate (mode) and a range can be computed for an input parameter, then it is possible to characterize the uncertainty with a triangular fuzzy number (possibility distribution) or a corresponding probability box bound by two uniform distributions. We use a five‐compartment Level I fugacity model and reported empirical data from the literature for three well‐known environmental pollutants (benzene, pyrene, and DDT) as illustrative cases for this evaluation. Propagation of uncertainty by discrete probability calculus or interval arithmetic can be done at a low computational cost and gives maximum flexibility in applying different approaches. Our evaluation suggests that the difference between fuzzy arithmetic and probability bounds analysis is small, at least for this specific case. The fuzzy arithmetic approach can, however, be regarded as less conservative than probability bounds analysis if the assumption of independence is removed. Both approaches are sensitive to repeated parameters that may inflate the uncertainty estimate. Uncertainty described by probability boxes was therefore also propagated through the model by Monte Carlo simulation to show how this problem can be avoided.     

The Impact of in-Service Training and Motivation on Job Performance of Technical & Vocational Education Teachers: Role of Person-Job Fit

In-service education and training (INSET), motivation and person-job fit of workers are considered vital for the performance of employees. The focused purpose of the study is to examine the associations between in-service training and motivation impact on job performance of Technical Vocational Education and Training (TVET) teachers, while examining the moderating role of person-job fit. Using convenience sampling technique, data is collected from TVET teachers in South Asia. The finding of this study revealed a significant impact for in-service training and motivation on job performance. This research study is useful for the HR managers and practitioners to utilize their employee’s true potential to get the desired results.

     

Risk analysis of fast spreading species in a Kashmir Himalayan National Park (Dachigam) for better monitoring and management

Huge economic costs and ecological impacts of invasive alien species (IAS) in the protected areas (PAs) worldwide make their timely prediction and potential risk assessment of central importance for effective management. While the preborder weed risk assessment framework has been extensively evaluated and implemented, the postborder species risk assessment framework has not been subjected to the same degree of scrutiny. Here we used a rather more realistic modified version of the Australian Weed Risk framework (AWRM) for Dachigam National Park (DNP) in Kashmir Himalaya against 84 plant species, including 55 alien species and 29 fast spreading native species, for risk analysis. We found two very high-risk species, three high-risk species, 10 medium-risk species, 29 low-risk species, and 40 negligible-risk species in the DNP. The containment scores accordingly ranged from 14.4 to 293.5 comprising of 27 species that can be contained with very high feasibility, 23 species with high feasibility, 14 species with medium feasibility, and 12 species which cannot be contained easily thereby having low feasibility of containment (FOC) score. However, eight species which have a negligible FOC score are difficult to contain within their infestation sites. Our results demonstrate the merit of the AWRM with a caution that the necessary region-specific modifications may help in its better implementation. Overall, these results provide quite a promising tool in the hands of protected area managers to timely and effectively deal with the problem of plant invasions.