M. Priya

Bio: M. Priya is an academic researcher from VIT University. The author has contributed to research in topics: Ontology (information science) & Ontology merging. The author has an hindex of 4, co-authored 14 publications receiving 76 citations.

Modular-multilevel converter topologies and applications – a review

Abstract: Recently developed modular-multilevel converter (M-MC) has a major attention in the industry and research works which is moving into feasible technology for many medium and high-power applications. M-MCs have been improved by existing power conversion technology in several aspects, including efficiency, modular structure, power quality, transformerless operational capability, fault tolerant and redundancy operations having a low expense, standard components utilisation, high availability, excellent quality of output wave forms. However, as several challenges combined with M-MC topologies, include reduced voltage stress, compact size, and substantially lower semiconductor losses. These attributes the lower operating cost for high-power applications such as distribution systems and high-voltage direct current (HVDC) transmission systems. The main contribution of this study is to bring the scrutiny of M-MC applications and different circuit topologies. These M-MC configurations consist of converter structures with sub-module converters and M-MC family members. In such a way, the M-MC applications are generalised and it results the size and cost halved, reduced conduction and switching losses and increases system reliabilities. Moreover, in each application of M-MC, drawbacks, and advantages have been discussed in detail. This review presents the latest performance of M-MC with respect to the mentioned research areas and new applications.

A Survey of State of the Art of Ontology Construction and Merging using Formal Concept Analysis

Abstract: The goal of Formal Concept Analysis (FCA) and Ontologies are modeling concepts with varying needs. An ontology is an explicit formal conceptualization of some domain of interest. Ontologies are widely used in various fields such as E-commerce, Semantic Web and knowledge management. FCA is a method of deriving a formal ontology or a concept hierarchy from a group of objects with their properties. FCA facilities an environment to make the data simpler by analyzing, structuring and visualizing. This paper presents a survey of Ontology construction and merging using FCA.

A novel method for merging academic social network ontologies using formal concept analysis and hybrid semantic similarity measure

Abstract: The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras is noticeably very high. With the availability of these ontologies, the needed information can be smoothly attained, but the presence of comparably varied ontologies nurtures the dispute of rework and merging of data. The assessment of the existing ontologies exposes the existence of the superfluous information; hence, ontology merging is the only solution. The existing ontology merging methods focus only on highly relevant classes and instances, whereas somewhat relevant classes and instances have been simply dropped. Those somewhat relevant classes and instances may also be useful or relevant to the given domain. In this paper, we propose a new method called hybrid semantic similarity measure (HSSM)-based ontology merging using formal concept analysis (FCA) and semantic similarity measure.,The HSSM categorizes the relevancy into three classes, namely highly relevant, moderate relevant and least relevant classes and instances. To achieve high efficiency in merging, HSSM performs both FCA part and the semantic similarity part.,The experimental results proved that the HSSM produced better results compared with existing algorithms in terms of similarity distance and time. An inconsistency check can also be done for the dissimilar classes and instances within an ontology. The output ontology will have set of highly relevant and moderate classes and instances as well as few least relevant classes and instances that will eventually lead to exhaustive ontology for the particular domain.,In this paper, a HSSM method is proposed and used to merge the academic social network ontologies; this is observed to be an extremely powerful methodology compared with other former studies. This HSSM approach can be applied for various domain ontologies and it may deliver a novel vision to the researchers.,The HSSM is not applied for merging the ontologies in any former studies up to the knowledge of authors.

An approach to merge domain ontologies using granular computing

Abstract: Granular computing is the emerging technique which performs data processing through making multiple levels of descriptions. Each level of description is expressed through granules or chunks of data also defined as information granules. The granule, the granule structure, and the granule layer are the heart of granular computing. Ontologies are vital information archives. On all disciplines of science and technology, ontologies are developed according to the requirements. Hence, the huge number of ontologies is available in the concerned domain which creates information duplication and storage problem. Merging of existing ontologies overcomes these issues. There are many merging approaches available. The existing approaches do not use granular computing for merging the ontologies. The proposed approach employs granular computing for merging the existing domain ontologies, thereby unifying multiple domain ontologies into a single representative domain ontology. For that, this research work proposes the following four granular computing processes, namely, association, isolation, purification, and reduction which can be applied over a group of similar nodes in the ontologies thereby unifying them. The proposed method achieves the ontology merging by performing two phases, namely similarity calculation phase and granular computing phase. The similarity calculation phase identifies the inter-label similarity between the labels of ontologies and computes the relevant group of nodes. Subsequently, granular computing applies association, isolation, purification, and reduction over a group of relevant nodes. The proposed approach is validated using the film industry and transportation domain ontologies and compared against its counterpart hybrid semantic similarity measure (HSSM). The results concluded that the proposed approach outperforms HSSM.

Circulating Current Control of Phase-Shifted Carrier-Based Modular Multilevel Converter Fed by Fuel Cell Employing Fuzzy Logic Control Technique

Abstract: The contribution of the modular multilevel converter (MMC) in integrating non-conventional energy sources into the grid is significant; the integration of fuel cells with distributed energy sources is especially prominent as they provide a constant voltage and current for constant load applications. Still, there is a high demand for a high-quality power conditioning unit since there is an occurrence of frequent power spikes. Further, the circulating current (CC) in phase legs is an inherent phenomenon of MMC that must be mitigated. Hence, this article proposed an MMC incorporating a fuzzy logic controller (FLC)-based technique to control the circulating currents. The fuzzy controller effectively reduced the harmonics of the CC in the dc-link system. In addition, phase-shifted carrier (PSC) modulation was employed for the MMC to improve the capacitor voltage balancing to maintain the constant input voltage. Moreover, a mathematical analysis of PSC modulation for MMC was performed to identify the PWM harmonic characteristics of the output voltage and the CC. The performance analysis of the proposed system was tested using the hardware in loop (HIL) simulation with the help of the real-time simulator OP-5700 to verify the feasibility.

Ontology-based concept similary in Formal Concept Analysis

Abstract: Both domain ontologies and Formal Concept Analysis (FCA) aim at modeling concepts, although with different purposes. In the literature, a promising research area concerns the role of FCA in ontology engineering, in particular, in supporting the critical task of reusing independently developed domain ontologies. With this regard, the possibility of evaluating concept similarity is acquiring an increasing relevance, since it allows the identification of different concepts that are semantically close. In this paper, an ontology-based method for assessing similarity between FCA concepts is proposed. Such a method is intended to support the ontology engineer in difficult activities that are becoming fundamental in the development of the Semantic Web, such us ontology merging and ontology mapping and, in particular, it can be used in parallel to existing semi-automatic tools relying on FCA.

Voltage Source Multilevel Inverters With Reduced Device Count: Topological Review and Novel Comparative Factors

Abstract: Multilevel inverters (MLIs) have gained increasing interest for advanced energy-conversion systems due to their features of high-quality produced waveforms, modularity, transformerless operation, voltage, and current scalability, and fault-tolerant operation. However, these merits usually come with the cost of a high number of components. Over the past few years, proposing new MLIs with a lower component count has been one of the most active topics in power electronics. The first aim of this article is to update and summarize the recently developed multilevel topologies with a reduced component count, based on their advantages, disadvantages, construction, and specific applications. Within the framework, both single-phase and three-phase topologies with symmetrical and asymmetrical operations are taken into consideration via a detailed comparison in terms of the used component count and type. The second objective is to propose a comparative method with novel factors to take component ratings into account. The effectiveness of the proposed method is verified by a comparative study.

Review of Multilevel Inverters for PV Energy System Applications

Abstract: Over the last decade, energy demand from the power grid has increased significantly due to the increasing number of users and the emergence of high-power industries. This has led to a significant increase in global emissions with conventional energy generation. Therefore, the penetration of renewable energy resources into the power grid has increased significantly. Photovoltaic systems have become the most popular resources as their protentional is enormous, thus, the worldwide installed PV capacity has increased to more than 635 gigawatts (GW), covering approximately 2% of the global electricity demand. Power electronics are an essential part of photovoltaic generation; the drive for efficient power electronic converters is gaining more and more momentum. Presently, multilevel inverters (MLI) have become more attractive to researchers compared to two-level inverters due to their abilities to provide lower electromagnetic interference, higher efficiency, and larger DC link voltages. This paper reviews multilevel inverters based on their classifications, development, and challenges with practical recommendations in utilizing them in renewable energy systems. Moreover, PV systems with various maximum power point tracking (MPPT) methods have been extensively considered in this paper as well. The importance and the development of a modified multilevel inverter are also highlighted in this review. In general, this paper focuses on utilizing multilevel inverters for PV systems to motivate and guide society to focus on inventing an efficient and economical multilevel inverter that has the combined capabilities of these converters reported in the literature.

Ontologies for Software Engineering: Past, Present and Future

Abstract: Background/Objectives: Research in recent years has probed integration amongst research field of Software Engineering & Semantic Web technology, addressing the advantages of applying Semantic techniques to the field of Software Engineering. Prolifically published studies have further substantiated the benefits of ontologies to the field of Software Engineering, which clearly motivate us to explore further opportunities available in this collaborated field. This paper is a survey expounding such opportunities while discussing the role of ontologies as a Software Life-Cycle support technology. Method/Statistical Analysis: Survey centred on providing an overview of the state-of-art of all the ontologies available for Software Engineering followed by their categorization based on software life cycle phases and their application scope. Findings: Characterization of ontologies as a Software Life-cycle support technology, instigated by the increasing need to investigate the interplay between Semantic Web & Software Engineering with the ultimate goal of enabling & improving Software Engineering capabilities. Application/Improvements: This paper discusses the practical and potential applications of ontologies in the field of Software Engineering followed by the issues and challenges that will keep this field dynamic and lively for years to come.