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1 – 10 of over 20000
Article
Publication date: 25 October 2022

Chen Chen, Tingyang Chen, Zhenhua Cai, Chunnian Zeng and Xiaoyue Jin

The traditional vision system cannot automatically adjust the feature point extraction method according to the type of welding seam. In addition, the robot cannot…

Abstract

Purpose

The traditional vision system cannot automatically adjust the feature point extraction method according to the type of welding seam. In addition, the robot cannot self-correct the laying position error or machining error. To solve this problem, this paper aims to propose a hierarchical visual model to achieve automatic arc welding guidance.

Design/methodology/approach

The hierarchical visual model proposed in this paper is divided into two layers: welding seam classification layer and feature point extraction layer. In the welding seam classification layer, the SegNet network model is trained to identify the welding seam type, and the prediction mask is obtained to segment the corresponding point clouds. In the feature point extraction layer, the scanning path is determined by the point cloud obtained from the upper layer to correct laying position error. The feature points extraction method is automatically determined to correct machining error based on the type of welding seam. Furthermore, the corresponding specific method to extract the feature points for each type of welding seam is proposed. The proposed visual model is experimentally validated, and the feature points extraction results as well as seam tracking error are finally analyzed.

Findings

The experimental results show that the algorithm can well accomplish welding seam classification, feature points extraction and seam tracking with high precision. The prediction mask accuracy is above 90% for three types of welding seam. The proposed feature points extraction method for each type of welding seam can achieve sub-pixel feature extraction. For the three types of welding seam, the maximum seam tracking error is 0.33–0.41 mm, and the average seam tracking error is 0.11–0.22 mm.

Originality/value

The main innovation of this paper is that a hierarchical visual model for robotic arc welding is proposed, which is suitable for various types of welding seam. The proposed visual model well achieves welding seam classification, feature point extraction and error correction, which improves the automation level of robot welding.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 21 October 2022

Antonella Estefania Bergesse, Alexis Rafael Velez, Liliana Cecilia Ryan and Valeria Nepote

The aim of this work was to evaluate the efficiency of subcritical conditions using different water–ethanol mixtures to recover antioxidant compounds from soybean seed…

Abstract

Purpose

The aim of this work was to evaluate the efficiency of subcritical conditions using different water–ethanol mixtures to recover antioxidant compounds from soybean seed coats (SSCs).

Design/methodology/approach

SSCs were subjected to high temperature and pressure conditions, using ethanol–water mixtures as extractive solvent, to obtain phenolic and flavonoid compounds with antioxidant activity. A mathematical model, namely one-site desorption kinetic model, was used to describe the extraction kinetics.

Findings

Temperature, solvent mass flow rate and solvent composition were studied, and the best extraction conditions were defined by a screening design. The maximum concentration of phenolics was obtained at 220 °C, 50% of ethanol and 2.5 g/min of solvent mass flow rate and a high antioxidant capacity toward different techniques was achieved. The one-site desorption kinetic model showed that before 30 min under optimal conditions, more than 90% of phenolics and flavonoids were recovered, a shorter extraction time than the commonly used at normal pressure and room temperature.

Originality/value

The seed coat is a major by-product of soybean processing, and it only markets as a low value ruminant feed. To date, there are no reports on the extract phenolics from SSCs by means of this methodology. The extraction technique described in this study provides a potential alternative for extraction of bioactive compounds from SSCs. This study contributes to adding value to this industrial waste and, ultimately, to optimize the postharvest production chain of soybean grains.

Details

British Food Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0007-070X

Keywords

Article
Publication date: 12 April 2022

Subhamoy Dhua, Kshitiz Kumar, Vijay Singh Sharanagat and Prabhat K. Nema

The amount of food wasted every year is 1.3 billion metric tonne (MT), out of which 0.5 billion MT is contributed by the fruits processing industries. The waste includes…

Abstract

Purpose

The amount of food wasted every year is 1.3 billion metric tonne (MT), out of which 0.5 billion MT is contributed by the fruits processing industries. The waste includes by-products such as peels, pomace and seeds and is a good source of bioactive compounds like phenolic compounds, flavonoids, pectin lipids and dietary fibres. Hence, the purpose of the present study is to review the novel extraction techniques used for the extraction of the bio active compounds from food waste for the selection of suitable extraction method.

Design/methodology/approach

Novel extraction techniques such as ultrasound-assisted extraction, microwave-assisted extraction, enzyme-assisted extraction, supercritical fluid extraction, pulsed electric field extraction and pressurized liquid extraction have emerged to overcome the drawbacks and constraints of conventional extraction techniques. Hence, this study is focussed on novel extraction techniques, their limitations and optimization for the extraction of bioactive compounds from fruit and vegetable waste.

Findings

This study presents a comprehensive review on the novel extraction processes that have been adopted for the extraction of bioactive compounds from food waste. This paper also summarizes bioactive compounds' optimum extraction condition from various food waste using novel extraction techniques.

Research limitations/implications

Food waste is rich in bioactive compounds, and its efficient extraction may add value to the food processing industries. Hence, compressive analysis is needed to overcome the problem associated with the extraction and selection of suitable extraction techniques.

Social implications

Selection of a suitable extraction method will not only add value to food waste but also reduce waste dumping and the cost of bioactive compounds.

Originality/value

This paper presents the research progress on the extraction of bioactive active compounds from food waste using novel extraction techniques.

Details

Nutrition & Food Science , vol. 52 no. 8
Type: Research Article
ISSN: 0034-6659

Keywords

Article
Publication date: 21 December 2021

Asli Kozan

This study aims to clarify the factors that act as a buffer to rent extraction from multi-national corporations (MNCs) in exchange relationships with the host country’s…

Abstract

Purpose

This study aims to clarify the factors that act as a buffer to rent extraction from multi-national corporations (MNCs) in exchange relationships with the host country’s political actors.

Design/methodology/approach

This study proposes a conceptual model of the factors that determine rent extraction by host country political actors from MNCs. The model identifies the sources of power the MNC can use to alleviate the power imbalance relative to the political actor to decrease rent extraction. Additionally, it identifies the factors that constrain the power-advantaged political actor, thus moderating the relationship between power imbalance and rent extraction.

Findings

This conceptual paper’s propositions remain for future empirical validation.

Originality/value

This study integrates insights from the international business literature and resource dependence theory (RDT) to identify the determinants of firm-specific rent extraction risk for MNCs. First, the model sheds light on the heterogeneity among MNCs in their susceptibility to rent extraction and their ability to manage their liability of foreignness in the host country. Second, by integrating the horizontal and vertical distribution of power in the political environment to analyze the power-dependence relationship between the MNC and host country political actors, the framework addresses a shortcoming of RDT and accounts for the dynamics of the external environment for MNCs managing their dependencies. This study also provides a basis for discussing the rent extraction MNCs face worldwide and lays the foundation for future empirical works.

Details

critical perspectives on international business, vol. 18 no. 5
Type: Research Article
ISSN: 1742-2043

Keywords

Article
Publication date: 9 August 2021

Xintong Zhao, Jane Greenberg, Vanessa Meschke, Eric Toberer and Xiaohua Hu

The output of academic literature has increased significantly due to digital technology, presenting researchers with a challenge across every discipline, including…

Abstract

Purpose

The output of academic literature has increased significantly due to digital technology, presenting researchers with a challenge across every discipline, including materials science, as it is impossible to manually read and extract knowledge from millions of published literature. The purpose of this study is to address this challenge by exploring knowledge extraction in materials science, as applied to digital scholarship. An overriding goal is to help inform readers about the status knowledge extraction in materials science.

Design/methodology/approach

The authors conducted a two-part analysis, comparing knowledge extraction methods applied materials science scholarship, across a sample of 22 articles; followed by a comparison of HIVE-4-MAT, an ontology-based knowledge extraction and MatScholar, a named entity recognition (NER) application. This paper covers contextual background, and a review of three tiers of knowledge extraction (ontology-based, NER and relation extraction), followed by the research goals and approach.

Findings

The results indicate three key needs for researchers to consider for advancing knowledge extraction: the need for materials science focused corpora; the need for researchers to define the scope of the research being pursued, and the need to understand the tradeoffs among different knowledge extraction methods. This paper also points to future material science research potential with relation extraction and increased availability of ontologies.

Originality/value

To the best of the authors’ knowledge, there are very few studies examining knowledge extraction in materials science. This work makes an important contribution to this underexplored research area.

Details

The Electronic Library , vol. 39 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 3 August 2021

Chuanming Yu, Haodong Xue, Manyi Wang and Lu An

Owing to the uneven distribution of annotated corpus among different languages, it is necessary to bridge the gap between low resource languages and high resource…

Abstract

Purpose

Owing to the uneven distribution of annotated corpus among different languages, it is necessary to bridge the gap between low resource languages and high resource languages. From the perspective of entity relation extraction, this paper aims to extend the knowledge acquisition task from a single language context to a cross-lingual context, and to improve the relation extraction performance for low resource languages.

Design/methodology/approach

This paper proposes a cross-lingual adversarial relation extraction (CLARE) framework, which decomposes cross-lingual relation extraction into parallel corpus acquisition and adversarial adaptation relation extraction. Based on the proposed framework, this paper conducts extensive experiments in two tasks, i.e. the English-to-Chinese and the English-to-Arabic cross-lingual entity relation extraction.

Findings

The Macro-F1 values of the optimal models in the two tasks are 0.880 1 and 0.789 9, respectively, indicating that the proposed CLARE framework for CLARE can significantly improve the effect of low resource language entity relation extraction. The experimental results suggest that the proposed framework can effectively transfer the corpus as well as the annotated tags from English to Chinese and Arabic. This study reveals that the proposed approach is less human labour intensive and more effective in the cross-lingual entity relation extraction than the manual method. It shows that this approach has high generalizability among different languages.

Originality/value

The research results are of great significance for improving the performance of the cross-lingual knowledge acquisition. The cross-lingual transfer may greatly reduce the time and cost of the manual construction of the multi-lingual corpus. It sheds light on the knowledge acquisition and organization from the unstructured text in the era of big data.

Details

The Electronic Library , vol. 39 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 13 April 2021

Mariana Souza Rocha, Luiz Célio Souza Rocha, Marcia Barreto da Silva Feijó, Paula Luiza Limongi dos Santos Marotta and Samanta Cardozo Mourão

The mucilage of the Linum usitatissimum L. seed (Linseed) is one of the natural mucilages that presents a great potential to provide a food hydrocolloid with potential…

Abstract

Purpose

The mucilage of the Linum usitatissimum L. seed (Linseed) is one of the natural mucilages that presents a great potential to provide a food hydrocolloid with potential applications in both food and pharmaceutical industries. To increase the yield and quality of linseed oil during its production process, it is necessary to previously extract its polysaccharides. Because of this, flax mucilage production can be made viable as a byproduct of oil extraction process, which is already a product of high commercial value consolidated in the market. Thus, the purpose of this work is to optimize the mucilage extraction process of L. usitatissimum L. using the normal-boundary intersection (NBI) multiobjective optimization method.

Design/methodology/approach

Currently, the variables of the process of polysaccharide extraction from different sources are optimized using the response surface methodology. However, when the optimal points of the responses are conflicting it is necessary to study the best conditions to achieve a balance between these conflicting objectives (trade-offs) and to explore the available options it is necessary to formulate an optimization problem with multiple objectives. The multiobjective optimization method used in this work was the NBI developed to find uniformly distributed and continuous Pareto optimal solutions for a nonlinear multiobjective problem.

Findings

The optimum extraction point to obtain the maximum fiber concentration in the extracted material was pH 3.81, temperature of 46°C, time of 13.46 h. The maximum extraction yield of flaxseed was pH 6.45, temperature of 65°C, time of 14.41 h. This result confirms the trade-off relationship between the objectives. NBI approach was able to find uniformly distributed Pareto optimal solutions, which allows to analyze the behavior of the trade-off relationship. Thus, the decision-maker can set extraction conditions to achieve desired characteristics in mucilage.

Originality/value

The novelty of this paper is to confirm the existence of a trade-off relationship between the productivity parameter (yield) and the quality parameter (fiber concentration in the extracted material) during the flaxseed mucilage extraction process. The NBI approach was able to find uniformly distributed Pareto optimal solutions, which allows us to analyze the behavior of the trade-off relationship. This allows the decision-making to the extraction conditions according to the desired characteristics of the final product, thus being able to direct the extraction for the best applicability of the mucilage.

Details

British Food Journal, vol. 123 no. 12
Type: Research Article
ISSN: 0007-070X

Keywords

Open Access
Article
Publication date: 14 August 2017

Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Anne H.H. Ngu and Yihong Zhang

This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.

1852

Abstract

Purpose

This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.

Design/methodology/approach

In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM) trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase). In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed.

Findings

Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed.

Originality/value

To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem) and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem). Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.

Details

PSU Research Review, vol. 1 no. 2
Type: Research Article
ISSN: 2399-1747

Keywords

Article
Publication date: 3 April 2017

Adrián Rabadán, Manuel Álvarez-Ortí, José E. Pardo, Ricardo Gómez, Arturo Pardo-Giménez and Miguel Olmeda

The high content of unsaturated fatty acids and the elevated presence of bioactive compounds make pistachio oil a healthy product with great commercial potential. One of…

Abstract

Purpose

The high content of unsaturated fatty acids and the elevated presence of bioactive compounds make pistachio oil a healthy product with great commercial potential. One of the primary constraints for its production is the lack of information regarding oil extraction from an industrial perspective. The purpose of this paper is to ensure the success of pistachio oil production at a commercial scale, attention should be paid to the effect of the main extraction procedures on the characteristics of oil, the consumer acceptance of these oils and their production cost.

Design/methodology/approach

Comparison and evaluation of the physicochemical and sensory characteristics and production cost of oil extracted using two different production lines (hydraulic press and screw press) are considered here.

Findings

Slight differences were found in the physicochemical analysis, but significant differences were identified in the sensory analysis. Consumer judges preferred the oil extracted with the hydraulic press. According to production costs, the break-even value that makes screw press extraction sustainable is €70.4 per litre, while for the hydraulic press it is €91.0 per litre, mainly due to a lower extraction yield and the longer extraction time required. As production costs of both methods are high, pistachio oil quality should prevail, making the use of the hydraulic press more advisable.

Originality/value

Although significant research has been conducted to analyse pistachio oil composition and nutritional value, little attention has been paid to differences that appear regarding consumer preferences and production costs depending on the production method used. This paper provides a comprehensive approach to high-quality pistachio oil production from an industrial perspective.

Details

British Food Journal, vol. 119 no. 4
Type: Research Article
ISSN: 0007-070X

Keywords

Article
Publication date: 14 August 2017

Sudeep Thepade, Rik Das and Saurav Ghosh

Current practices in data classification and retrieval have experienced a surge in the use of multimedia content. Identification of desired information from the huge image…

Abstract

Purpose

Current practices in data classification and retrieval have experienced a surge in the use of multimedia content. Identification of desired information from the huge image databases has been facing increased complexities for designing an efficient feature extraction process. Conventional approaches of image classification with text-based image annotation have faced assorted limitations due to erroneous interpretation of vocabulary and huge time consumption involved due to manual annotation. Content-based image recognition has emerged as an alternative to combat the aforesaid limitations. However, exploring rich feature content in an image with a single technique has lesser probability of extract meaningful signatures compared to multi-technique feature extraction. Therefore, the purpose of this paper is to explore the possibilities of enhanced content-based image recognition by fusion of classification decision obtained using diverse feature extraction techniques.

Design/methodology/approach

Three novel techniques of feature extraction have been introduced in this paper and have been tested with four different classifiers individually. The four classifiers used for performance testing were K nearest neighbor (KNN) classifier, RIDOR classifier, artificial neural network classifier and support vector machine classifier. Thereafter, classification decisions obtained using KNN classifier for different feature extraction techniques have been integrated by Z-score normalization and feature scaling to create fusion-based framework of image recognition. It has been followed by the introduction of a fusion-based retrieval model to validate the retrieval performance with classified query. Earlier works on content-based image identification have adopted fusion-based approach. However, to the best of the authors’ knowledge, fusion-based query classification has been addressed for the first time as a precursor of retrieval in this work.

Findings

The proposed fusion techniques have successfully outclassed the state-of-the-art techniques in classification and retrieval performances. Four public data sets, namely, Wang data set, Oliva and Torralba (OT-scene) data set, Corel data set and Caltech data set comprising of 22,615 images on the whole are used for the evaluation purpose.

Originality/value

To the best of the authors’ knowledge, fusion-based query classification has been addressed for the first time as a precursor of retrieval in this work. The novel idea of exploring rich image features by fusion of multiple feature extraction techniques has also encouraged further research on dimensionality reduction of feature vectors for enhanced classification results.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 10 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

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