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This paper aims to accurately estimate harmonics/interharmonics in modern power system. There are several high spectral resolution techniques that have been in use for several years like Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Prony methods, etc. but these techniques require prior knowledge of number of modes present in the signal. Model Order (MO) estimation techniques have to make a trade-off between accuracy and their speed i.e., computational burden. Therefore, there is always a requirement of a technique that is fast as well as accurate.

The proposed standard deviation (SD) method eliminates the requirement of energy validation test and analyses the distribution pattern, i.e. standard deviation of eigenvalues to identify the number of modes present in the signal. Signal is reconstructed using estimated modes and reconstruction error is obtained to show accuracy of the proposed estimation.

Six test synthetic signals as well as one practical signal have been taken for validating the proposed method. The paper shows that proposed methodology has a better accuracy compared to modified exact model order (MEMO) method in high noise environment and takes very less computation time compared to the exact model order (EMO) method.

The proposed method has been practically implemented for harmonic/interharmonic analysis at a sewage treatment plant at GIFT City, Gujarat, India. Apart from this the proposed method is modeled in python-based tool and is run into low-cost Raspberry Pi like hardware to create an onsite as well as remote monitoring device.

SD-based approach for model order estimation is novel to this area. Further, the proposed method is compared with EMO and MEMO under varying noise conditions to check for accuracy and estimation time.

In innovation management, the complexity inherited in the supply network may be necessary for success. This study aims to holistically examine innovation complexities and system attractors within a hierarchically nested supply network and explore how they dynamically interact and influence adaptive innovation processes.

Taking a complexity theory perspective, we employed a methodological bricolage approach using a single case study with multiple embedded units of analysis – namely, a supply network encompassing 36 firms. We drew upon primary data obtained from 42 interviewees and rich secondary data, and we employed a temporal exponential random graph model to examine the micro-foundations of the evolution of the sampled supply network over a decade.

This study presents a comprehensive overview of the innovation complexities—relational, temporal, dynamic, operational and structural – and how they manifest within a supply network. It also identifies three systemic attractors – point, periodic and strange – and elucidates their relationships with the complexities and their impact on innovative supply network dynamics. The resulting conceptual framework and working propositions provide a detailed perspective on the complex interplay between balanced order and chaos and the potentially unbalanced innovation states within a supply network.

This research offers an in-depth perspective on the innovation complexities and dynamic attractors within a supply network from a holistic, multilevel perspective. It advances complexity theory and deepens the understanding of supply networks as complex adaptive systems.

Industries, especially power plants, using steam as power fluid employ many equipment and systems using saturated steam. Mathematical modeling of this saturated steam water space (SSWS) equipment is important for simulators catering to these industries and power plants. Single-equation-based modeling approach and its optimized version, mass factor–volume factor approach, are very efficient in modeling SSWS with bounded volumes, where the volume of the space is fixed. In unbounded volumes, the volume may be changing or is unbounded because of expansion, contraction or pressure control. The purpose of this paper is to propose a single equation based modeling approach for unbounded SSWS. Such unbounded volumes are encountered in coolant channels of pressurized heavy water reactor (PHWR)-type nuclear power plants (NPPs).

This paper proposes an extension of a single-equation approach by considering a subsection of the volume as miniature Point SSWS. In the proposed Point SSWS, the total heat, mass and volume of the SSWS are delinked and overall density and heat density are introduced in place. With this extension, Point SSWS can be applied to unbounded volumes.

In this study, 392 coolant channels of proposed 680 MWe PHWR have been simulated to ascertain the overall coolant density when coolant boils partially on nuclear heating. The simulation results have been compared with simulation results available from previous researchers and it has been found that the values are in line with previous researchers with maximum deviation of 1.2 per cent.

From the simulation results and their low value of deviation, it is clear that point space approach can be effectively used in modeling Point SSWS. Moreover, theoretically, it has been proved that the density of homogenous steam–water mixture is dependent only on the bulk heat density and temperature of the mixture.

The purpose of this paper is to examine the social and behavioral actions, activities and practices in order to group them together to create behavior‐based profiles that characterize the various stages of the innovation generation processes within organizations.

Qualitative data were collected from nine Australian companies from the biotechnology sector. Using the grounded theory approach to data analysis, labels from Rogers' adopter categorization model were used to broadly identify and classify typical actions, activities, practices and behaviors exhibited within organizations that can be described as being “innovator”, “early adopter”, “early majority”, “late majority” or “laggard” types. Further, Moore's metaphor of “chasm” was applied to explore the nature of difficulties that organizations face in converting innovative ideas into commercially successful products and services.

The use of the labels from the categories of the adopter categorization model enabled suitable behavior‐based profiles to be developed.

The use of the adopter categorization model provides a fuller and richer insight into the innovation generation process. The model can also be used to assess more holistically the viability of innovations as they progress from inception to commercialization.

A literature review within the manufacturing strategy (MS) discipline with a focus on thematic developments is provided. Based on recent studies, a set of challenges posed to manufacturing enterprise of the future are summarized, and thematic areas are analyzed in relation to meeting those challenges. The paper aims to discuss these issues.

Based on a select set of 506 articles published in top-ranked refereed international journals in the discipline of operations management, major and subthemes are identified and the publication trends in these themes are provided with time and across geographical regions, namely: North America, Europe, and other parts of the world.

MS literature is predominantly focussed on the economic objectives of firms without a due focus on the social and environmental perspectives. MS literature covers 11 major thematic areas, namely: MS components and paradigms, manufacturing capabilities (MCs), strategic choices (SCs), best practices (BPs), the strategy process (SP), supply-chain management (SCM), performance measurement, transnational comparisons, global manufacturing, environmental/green manufacturing, and literature reviews. The research in two areas – SCs, and MCs – has been in decline, while the research in BPs, the SP, and transnational comparisons is growing (in absolute figures). Various research opportunities for future studies are identified.

The literature review is limited in its selection of articles and journals, however, the identified trends clarify the state of research by the MS research community at large.

For researchers, multiple new research directions are identified in order to advance knowledge in the field of MS. The publication trends also highlight thematic areas where most of the MS body of knowledge is currently available and can be utilized by practitioners.

The paper’s novelty comes from: first, a broader and deeper review of thematic areas that has not been researched before, second, trends in thematic areas by time, across geographical regions, and including time-region dyads, and third, coverage provided by MS literature in meeting challenges posed to manufacturing enterprise of the future.

Rapid prototyping technologies have introduced a new generation of rapid tooling processes. Many of these rapid tools have been used for injection moulding where the thermal properties of the tool material are critical to the quality of parts produced. Rapid tools are often made from materials with substantially different thermal properties than conventional metal tools. Engineers wishing to make use of these technologies to produce technical prototypes must be aware of the effect this will have on final part properties. Some previous research has been undertaken in this area. Reviews the work done in the field of rapid tooling used for injection moulding. The review shows that, whereas a range of techniques and final part materials has been studied, the results obtained are incomplete and often unexplained. The authors draw conclusions as to why this is so and go on to identify areas for further work that will be pursued.

The study aims to propose a predictive model that combines personality and demographic factors to predict student academic performance (SAP). This research study works on understanding, enhancing and applying techniques to enhance the prediction of SAP.

The authors gathered information from 305 university students from Al-Zintan University Libya. The study uses a survey questionnaire to collect data on essential variables. The purpose of the questionnaire is to discover variables that affect students' academic performance. The survey questionnaire has 44 closed questions with Likert scale designs that were distributed to a variety of college students at the start of the first semester of 2022. It includes questions about demographics, personality, employment and institutional aspects. The authors proposed a predictive model to identify the main fundamental components, consisting of one dependent variable (SAP) and five independent constructs. The suggested model is tested using partial least squares (PLS) and structural equation modeling (SEM), which perform better than covariance-based structural equation modeling (CB-SEM). PLS-SEM performs well with smaller sample sizes, even for complicated models.

The study results show that the proposed model accurately predicted the student's academic performance. The personality trait variables are a key factor that determines the actual student's academic performance. The student's academic performance is significantly impacted by each variable in the personality trait variables as well.

The process of validating research was done empirically through the accuracy and efficiency of model performance. The study differs from previous studies in that it accumulated a wide range of factors from different dimensions, including student demographics and personality trait factors. The authors developed a structural equation model to predict students' academic performance.

The purpose of this study is to explore the coopetition relationships between platform owners and complementors in complementary product markets. Drawing on the coopetition theory, the authors examined the evolutionary trends of the coopetition relationships between platform owners and complementors and explore the main influence factors.

The authors used Lotka–Volterra model to analyze the coopetition relationship between platform owners and complementors, including the evolutionary trends as well as the results. Considering the feasibility of sample data collection, simulation is used to verify the effects of different factors on the evolution of coopetition relationships.

The results show that there are four possible results of the competition in the complementary products market. That comprises “winner-take-all for platform owners,” “winner-take-all for complementors,” “stable competitive coexistence” and “unstable competitive coexistence,” where “stable competitive coexistence” is the optimal evolutionary state. Moreover, the results of competitive evolution are determined by innovation subjects’ interaction parameters. However, the natural growth rate, the initial market benefits of the two innovators and the overall benefits of the complementary product markets influence the time to reach a steady state.

The study provides new insights into the entry of platform owners into complementary markets, and the findings highlight the fact that in complementary product markets, platform owners and complementors should seek “competitive coexistence” rather than “winner-takes-all.” Moreover, the authors also enrich the coopetition theory by revealing the core factors that influence the evolution of coopetition relationships, which further enhance the analysis of the evolutionary process of coopetition relationships.

The purpose of this paper is to report an investigation of local sustainable production in Australia and Sweden aimed at exploring the factors contributing to survival and competitiveness of manufacturing companies.

In Australia, six companies were studied in 2010, with comparisons being made with three of them from earlier projects. In Sweden, eight manufacturing companies were studied on two occasions 30 years apart, in 1980 and 2010. To provide a valid comparative perspective a common format for data collection and analysis was used.

There has been a shift in the nature of competition in both Sweden and Australia due to an increasing complexity of the global business environment as well as changes in technology and customer expectations. Despite the differences in country context, the findings suggest that all the manufacturing companies have a good awareness of the elements of the market environment and the relationships with their competitive strategy. However, in general, the Swedish companies have more experience of managing the risks and benefits from operating in the international environment.

The results of the research are based on a relatively small sample of case companies in a limited number of industrial sectors. There are methodology implications for future research in the area.

The research results have practical implications for the manufacturing industry, especially for companies operating in a competitive international environment.

The paper is based on original case research and comparative analysis of data from different geographical contexts. It contributes to both theory and management practice about the strategic resources, decision choices, competitive environments and firm values needed to address external market demands as well as in building internal capabilities.