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This paper aims to address the issue of matching controlled vocabulary on agroforestry from knowledge organization systems (KOS) and incorporating these terms in DITA markup. The paper has been selected for an extended version from MTSR'11.

After a general description of the steps taken to harmonize controlled vocabulary on agroforestry, a general discussion of related work enriching documents and matching controlled vocabularies as well as details on managing controlled vocabulary in DITA are provided.

The paper identifies a number of practical and theoretical issues in matching controlled vocabulary from different sources, e.g. the complexity of addressing inconsistencies and incompatibilities between systems, and came across a number of approaches to semantically enrich documents, such as semantic‐document approach, facet classification, and integrating metadata and markup in documents.

Ways of incorporating controlled vocabularies into DITA markup are presented that can be drawn upon to guide future work in this area.

No previous work has reflected on the actual experience used to enrich DITA markup, especially with reference to the agrorestry domain.

Among the proposed radio access strategies for improving system execution in 5G networks, the non-orthogonal multiple access (NOMA) scheme is the prominent one.

Among the most fundamental NOMA methods, power-domain NOMA is the one where at the transmitter, superposition coding is used, and at the receiver, successive interference cancellation (SIC) is used. The importance of power allocation (PA) in achieving appreciable SIC and high system throughput cannot be overstated.

This research focuses on an outage probability analysis of NOMA downlink system under various channel conditions like Rayleigh, Rician and Nakagami-m fading channel. The system design's objectives, techniques and constraints for NOMA-based 5G networks' PA strategies are comprehensively studied.

From the results of this study, it is found that the outage probability performance of downlink ordered NOMA under Rayleigh, Rician and Nakagami-m fading channel was good.

Outage probability analysis of downlink ordered NOMA under various channel conditions like Rayleigh, Rician and Nakagami-m fading channels were employed. Though the performance of Nakagami-m fading channel is lesser compared to Rayleigh channel, the performance for user 1 and user 2 are good.

The paper aims to develop a prototype middleware framework between different terminology resources in order to provide a subject cross‐browsing service for library portal systems.

Nine terminology experts were interviewed to collect appropriate knowledge to support the development of a theoretical framework for the research. Based on this, a simplified software‐based prototype system was constructed incorporating the knowledge acquired. The prototype involved mappings between the computer science schedule of the Dewey Decimal Classification (which acted as a spine) and two controlled vocabularies, UKAT and ACM Computing Classification. Subsequently, six further experts in the field were invited to evaluate the prototype system and provide feedback to improve the framework.

The major findings showed that, given the large variety of terminology resources distributed throughout the web, the proposed middleware service is essential to integrate technically and semantically the different terminology resources in order to facilitate subject cross‐browsing. A set of recommendations are also made, outlining the important approaches and features that support such a cross‐browsing middleware service.

Cross‐browsing features are lacking in current library portal meta‐search systems. Users are therefore deprived of this valuable retrieval provision. This research investigated the case for such a system and developed a prototype to fill this gap.

This paper aims to focus on the basic principle of WO₃ gas sensors to achieve high gas-sensing performance with good stability and repeatability. Metal oxide-based gas sensors are widely used for monitoring toxic gas leakages in the environment, industries and households. For better livelihood and a healthy environment, it is extremely helpful to have sensors with higher accuracy and improved sensing features.

In the present review, the authors focus on recent synthesis methods of WO₃-based gas sensors to enhance sensing features towards toxic gases.

This work has proved that the synthesis method led to provide different morphologies of nanostructured WO₃-based material in turn to improve gas sensing performance along with its sensing mechanism.

In this work, the authors reviewed challenges and possibilities associated with the nanostructured WO₃-based gas sensors to trace toxic gases such as ammonia, H₂S and NO₂ for future research.

The study attempts to capture the comprehensive accounting framework of the inverted U-shaped Environmental Kuznets Curve (EKC) hypothesis relevant for an emerging economy based on an emission-growth decoupling approach. The paper intends to re-examine and analyze the roles of influential production- and consumption-based drivers for the prominently observable increasing pattern of the energy-related carbon dioxide (CO₂) emissions from the Indian Territory.

The study adopted an annual time series structural decomposition analysis (SDA) based on a single-country input-output framework for the period 2000–2014 to identify and elaborate the contribution of the responsible drivers to the production-based carbon emission of India. The study further proceeded to analyze a decoupling index to explore the features of economic growth and carbon emissions comovement over time.

The results from the empirical exercise reflect a pattern of consistently developing relative decoupling character for most of the production-based drivers. The paper produces insightful results on the pattern of energy-related CO₂ emissions from the perspective of the EKC hypothesis and highlights the importance of consumption-based drivers as substantial contributors to the economy-wide CO₂ emissions to be controlled for effective decoupling of the aggregate production-based CO₂ from the volume of aggregate production to enhance the opportunities for sustainable economic development.

The study uniquely correlates the declining trend of the emission intensity of India's gross domestic product (GDP) and the inclining trend of the overall emissions due to ever-increasing gross output in the form of a comprehensive accounting relationship.

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.

This study’s analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians’ theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures’ suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness.

This study’s results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity.

The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study’s results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

The paper aims to investigate issues surrounding publishing thesauri as linked data and explores a systematic way for publishing linked open thesauri

Based on the four principles of linked data, a novel approach is proposed to incorporate terminology services with thesauri and provide more descriptive information about thesauri and relating services. A proof-of-concept system was built for demonstrating the approach.

Carefully designed URIs and terminology services are necessary for publishing linked open thesauri. However, there is still a lack of standards for describing linked open thesauri and terminology services. Since it is possible to publish thesauri at the hands of creators and maintainers, distributed thesauri may be a good complement to the traditional registry approach.

Only a simple knowledge organisation system (SKOS) core model is considered in the paper. There may be some adjustment for applying the findings to thesauri using the SKOS extended model and other models.

The paper proposes a more systematic way for publishing linked open thesauri. It is important to consider a linked open thesaurus as a dynamic system rather than a static data dump. In addition, functionality for using thesauri is equally important for publishing thesauri.

The purpose of this research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to identify risks and improve risk control efficiency during the development phase.

A novel framework for quality risk evaluation in complex equipment is proposed, which integrates probabilistic hesitant fuzzy set-quality function deployment (PHFS-QFD) and grey clustering. PHFS-QFD is applied to identify the quality risk factors, and grey clustering is used to evaluate quality risks in cases of poor quality information during the development stage. The unfolding function of QFD is applied to simplify complex evaluation problems.

The methodology presents an innovative approach to quality risk evaluation for complex equipment development. The case analysis demonstrates that this method can efficiently evaluate the quality risks for aircraft development and systematically trace back the risk factors through hierarchical relationships. In comparison to traditional failure mode and effects analysis methods for quality risk assessment, this approach exhibits superior effectiveness and reliability in managing quality risks for complex equipment development.

This study contributes to the field by introducing a novel theoretical framework that combines PHFS-QFD and grey clustering. The integration of these approaches significantly improves the quality risk evaluation process for complex equipment development, overcoming challenges related to data scarcity and simplifying the assessment of intricate systems.