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The purpose of this paper is to investigate the condition of insulation in high-voltage equipments using partial discharge (PD) measurements. It proposes the methods to eliminate several noises like white noise, random noise and discrete spectral interferences which severely pollutes the PD signals. The study aims to remove these noises from the PD signal effectively by preserving the signal features.

This paper employs fast Fourier transform, discrete wavelet transform and translational invariant wavelet transform (TIWT) for denoising the PD signals. The simulated damped exponential pulse and damped oscillatory pulse with low- and high-level noises and a measured PD signal are considered for this analysis. The conventional wavelet denoising approach is also improved by estimating the automated global optimum threshold value using genetic algorithm (GA). The statistical parameters are evaluated and compared. Among these methods, GA-based TIWT approach provides robustness and reduces computational complexity.

This paper provides effective condition monitoring of power apparatus using GA-based TIWT approach. This method provides the low value of mean square error, pulse amplitude distortion and also high reduction in noise level due to its robustness and reduced computational complexity. It suggests that this approach works well for both signals immersed in noise as well as for noise immersed in signals.

Because of the chosen PD signals, the research results may lack for multiple discharges. Therefore, researchers are encouraged to test the proposed propositions further.

The paper includes implication for the development of online testing for equipment analysis and diagnostics during normal operating condition. Corrective actions can be planned and implemented, resulting in reduced unscheduled downtime.

This PD-based analysis often present well in advance of insulation failure, asset managers can monitor it over time and make informed strategic decisions regarding the repair or replacement of the equipment. These predictive diagnostics help society to prioritize investments before an unexpected outage occurs.

This paper provides an enhanced study of condition monitoring of HV power apparatus by which life time of insulation can be increased by taking preventive measures.

Indian railways (IR) is one of the largest railway networks in the world. As a part of its strategic development initiative, demand forecasting can be one of the indispensable activities, as it may provide basic inputs for planning and control of various activities such as coach production, planning new trains, coach augmentation and quota redistribution. The purpose of this study is to suggest an approach to demand forecasting for IR management.

A case study is carried out, wherein several models i.e. automated autoregressive integrated moving average (auto-ARIMA), trigonometric regressors (TBATS), Holt–Winters additive model, Holt–Winters multiplicative model, simple exponential smoothing and simple moving average methods have been tested. As per requirements of IR management, the adopted research methodology is predominantly discursive, and the passenger reservation patterns over a five-year period covering a most representative train service for the past five years have been employed. The relative error matrix and the Akaike information criterion have been used to compare the performance of various models. The Diebold–Mariano test was conducted to examine the accuracy of models.

The coach production strategy has been proposed on the most suitable auto-ARIMA model. Around 6,000 railway coaches per year have been produced in the past 3 years by IR. As per the coach production plan for the year 2023–2024, a tentative 6551 coaches of various types have been planned for production. The insights gained from this paper may facilitate need-based coach manufacturing and optimum utilization of the inventory.

This study contributes to the literature on rail ticket demand forecasting and adds value to the process of rolling stock management. The proposed model can be a comprehensive decision-making tool to plan for new train services and assess the rolling stock production requirement on any railway system. The analysis may help in making demand predictions for the busy season, and the management can make important decisions about the pricing of services.

Human gait analysis is based on a significant part of the musculoskeletal, nervous and respiratory systems. Gait analysis is widely adopted to help patients increase community involvement and independent living.

This paper presents a system for the classification of abnormal human gaits using a Markerless 3D Motion Capture device. This study aims at examining and estimating the spatiotemporal and kinematic parameters obtained by 3D gait analysis in diverse groups of gait-impaired subjects and compares the parameters with that of healthy participants to interpret the gait patterns.

The classification is based on mathematical models that distinguish between normal and abnormal gait patterns depending on the deviations in the gait parameters. The difference between the gait measures of the control and each disease group was examined using 95% limits of agreement by the Bland and Altman method. The scatter plots demonstrated gait variability in Parkinsonian and ataxia gait and knee joint angle variation in hemiplegic gait when compared with those of healthy controls. To prove the validity of the Kinect camera, significant correlations were detected between Kinect- and inertial-based gait tests.

The various techniques used for gait assessments are often high in price and have existing limitations like the hindrance of components. The results suggest that the Kinect-based gait assessment techniques can be used as a low-cost, less-intrusive alternative to expensive infrastructure gait lab tests in the clinical environment.

The increasing importance of health food sales and the growing number of consumers purchasing health foods necessitates that marketers develop enhanced understanding of health food consumers. The purpose of this paper is to provide a theoretical extension to the health belief model (HBM) that integrates personal stress and environmental cues (visible health problems) with its constructs.

Data were collected through a quantitative face-to-face survey of 384 health food consumers in Taiwan, and structural equation modelling was used to analyse the data.

The results show that the perceived benefits and barriers of health foods are critical antecedents of continued-consumption intention. Personal stress and visible health problems substantially influence consumers’ perceived susceptibility to and severity of health problems, and perceived susceptibility consequently leads to consumer continued consumption. However, the results indicate an irrelevant relationship between perceived severity of health problems and continued-consumption intentions.

Based on the HBM, the authors integrated perceived stress and visible health problems into the health food consumer research. The findings can improve the understanding of managers in the health food market regarding the role that stress and visibility play in consumer decisions.

People are increasingly concerned about food and health and are seeking enriched products. One way to add nutritional value to yogurt consists of the addition of nutritional flour. However, it is necessary to optimize formulations that meet the consumers’ expectations. Thus, the purpose of this paper is to aim at sensory optimization of a strawberry yogurt enriched with different flours.

The optimal concentrations of each flour were defined using the Just-about-right-scale test. Then, an acceptance test was used to assess the samples at optimal concentrations.

It was observed that the strawberry yogurt should include 1.275 percent golden flaxseed flour, 1.093 percent green banana flour, 1.075 percent eggplant flour and 3.420 percent oatmeal flour. All formulations had good acceptability and the yogurt added with the addition of golden flax flour and the traditional product received similar sensory acceptance. Thus, it is possible to add nutritional value to strawberry yogurt by maintaining its sensory quality.

More detailed studies on the shelf-life of yogurt are necessary to enable the incorporation of flours into yogurt as heat, light and oxygen can reduce the beneficial effects of flours. Therefore, researchers should test the proposed propositions further.

Optimization of an enriched yogurt is a good alternative to provide a product that meets consumers’ expectations, besides adding value to the product. However, there are technological challenges when adding functional components in foods. Thus, this study aimed at sensory optimization of a strawberry yogurt enriched with different flours.

The authors aimed to provide a healthy product to the market as well as contribute toward product variety in the market.

There are few studies in respect to the sensory aspects of enriched yogurts. Therefore, this work will aid future studies, supporting the optimization of functional products and contributing toward product variety in the market.

The volatile nature of foreign portfolio flows, especially flows into debt market, has large implications on financial and macroeconomic stability in recipient countries. It is necessary to identify the main drivers of portfolio investments in bond market of developing economies to design effective policies to enhance resilience of the economy and help in managing capital flow volatility. The determinants of foreign portfolio investment to Indian equity market have been examined in literature, but flows to bond market remain unexplored. Thus, the purpose of this paper is to identify the possible determinants of foreign portfolio flows to Indian bond market both in the short and in the long run.

This study carries out a time series analysis by deploying autoregressive distributed lag (ARDL) approach to cointegration of monthly data of the period from January 2002 to December 2016 for the Indian economy. A mix of pull and push factors has been analysed in this study. Domestic growth, domestic stock market performance, interest rate differential, exchange rate, volatility in exchange rate, stock market returns in other emerging economies, foreign output growth and dummy variables to trace the external developments such as global financial crisis and unconventional monetary policies of advanced economies have been used as explanatory variables.

The dominant pull factor such as interest rate differential explains the dynamics of flows in Indian bond market. The relationship between capital movements and interest rate differentials is the most accepted paradigm in international finance (Haynes, 1988). Among other domestic factors are stock market performance, volatility in exchange rates and domestic growth rates which are found to be significant drivers of foreign portfolio bond flows to India. The study also confirmed that global conditions could induce a fast outflow of capital from India.

The study concludes that both domestic factors and external factors are equally important in determining the foreign portfolio investments in the Indian debt market.

The empirical analysis conducted in this study suggests that direct and indirect measures can be taken to increase and stabilise foreign investments in the Indian bond market. Direct policy measures refer to those tools which are under the ambit of policymakers. Indirect measures comprise those tools that are not under the direct control of the fiscal and monetary authorities but require coordinated efforts of the government and private sector. In this context, strengthening of not only financial and economic but also administrative institutions will be necessary. Creditworthiness and policy credibility should be improved to address erratic foreign portfolio investment in debt market of India.

This study is an original research study. This study adds to the existing literature and is expected to guide policymakers on the specific aspect of the management of capital flows as it gets affected by changes in monetary and fiscal policies.

The purpose of this paper is to study the influence of fibre properties on filtration behavior. Air pollution is a major threat to human beings due to industrialization and urbanization. Among various particles in the atmospheric air, PM 2.5 causes various respiratory problems to human beings and also causes premature engine wear. The primary importance for the filters is higher filtration efficiency with lower pressure drop.

In this research, nonwoven filters were developed with different diameters of polyester fibres such as 0.8d, 1.2d and 6d fibres and different proportions of fibres were used. The Kuwabara cell model was used to derive certain parameters and its effects were analysed. The effect of basis length, solid volume fraction and porosity on filtration behavior was discussed in detail.

The filtration efficiency is higher for particle size from 1–3 µm, when different layers of polyester fibres are used with coarser fibres as the top layer and finer as the bottom layer. The filtration performance is better for layered nonwoven than unimodal nonwoven. The higher proportion of micro-denier fibres results in higher filtration efficiency with higher pressure drop.

The proposed research is more suitable for the particle size of more than 1 µm because of the fibre diameters and its achievable porosity. The filtration efficiency can be increased further by increasing the mass per unit area, which also increases the pressure and is not recommended.

The effect of triple-layers with different diameters of fibres on filtration was analysed. Due to the variation in diameters of fibres in different layers, the filtration performance varies.

This research focuses on the development and characterization of oil-wetted spun-bonded polypropylene (PP) non-woven filters for improved air intake systems in automobiles. The study aims to enhance engine performance, durability, fuel economy and emission reduction by addressing key aspects such as contaminants filtration efficiency, loading capacity, pressure drop, temperature performance and longevity.

The research methodology involves the utilization of textile fabrics, particularly oil-wetted spun-bonded PP non-woven filters, renowned for their effective particle collection capability from intake air. Experiments were conducted using a Box–Behnken design with three variables – oil concentration, areal density and dust quantity – each at three different levels to establish correlations with the filter’s dust holding capacity (DHC) and pressure drop.

The findings indicate that immersing particles in oil-coated medium significantly enhances the filter’s DHC. Notably, castor oil as a coating demonstrates remarkable results, with a 97.53% increase in DHC and a high particulate matter filtration efficiency of 94.12%.

This study contributes to the originality of research by emphasizing the importance of oil density in determining the filter’s DHC and filtration efficiency. Furthermore, it highlights the superiority of castor oil over coconut oil-coated filter media, advancing air intake and/or filter systems for automotive engines.

People are increasingly concerned about food and health and seek for functional and sugar-free products. However, there are technological challenges when adding functional components and substituting sugar in foods. Thus, the purpose of this paper is to evaluate the influence of packaging and storage time on the sensory profile of functional diet guava preserve added with prebiotics, supporting the development of functional and sugar-free products and contributing to the product variety in the market.

A two-factor full factorial design was conducted in triplications that evaluated transparent and opaque packaging vs storage time (six months). The products were stored in packages with different light permeability (transparent and opaque). Quantitative descriptive analysis (QDA) and acceptance tests were performed.

The packaging material did not affect the sensory changes of functional diet guava preserve during the six months of storage. QDA test showed that from three months of storage the original characteristics of the product were lost and a slight decrease in overall acceptance was observed after four and six months. However, during the six months the products had good acceptance; consequently, it was not possible to establish their rejection before this period.

More detailed studies regarding a longer storage period, including the physical and chemical measurements must be done to clarify other points about the influence of packaging and storage time on the sensory profile of functional diet guava preserve added with prebiotics. Therefore, researchers are encouraged to test the proposed propositions further.

The development of a functional and sugar-free preserve is a good alternative to provide a product that meets the actual consumer desires and adds value to the product. However, there are technological challenges when adding functional components and substituting sugar in foods. Thus, this study provides important information for the development of sugar-free and functional products, and to prolong their shelf life.

There are few studies with respect to the sensory aspects during the storage of functional preserves. Thus, this work will aid future studies, supporting the development of functional and sugar-free products and contributing to the product variety in the market.