Abstract We study the relationships between arms imports, political stability, oil exports, gross domestic product, and greenhouse gas emissions by considering a panel of eight oil-exporting countries of the Gulf region and yearly data between 2000 and 2023. Since there is cross-sectional dependence between our considered variables, second-generation panel unit root and cointegration tests are used. In addition, we use the cross-sectional distributed lag (CS-DL) methodology to estimate our long-run coefficients. Several new and interesting results are deduced. Arms imports increase political stability and economic growth. Political stability increases oil exports and reduces greenhouse gas emissions. Oil exports reduce arms imports. Oil-exporting Gulf countries are advised to continue importing and plan the production of high-tech weapons to strengthen their political stability. This latter enables them to elaborate and realize energy efficiency and renewable energy strategies, transforming them into producing and exporting renewable energy countries. Jel classification: C33; H56; O53 ; Q37 ; Q54.
Abstract We consider the relationships between military expenditures, arms imports, political stability, oil exports, gross domestic product, and greenhouse gas emissions in a panel of six oil-exporting countries of the Gulf region and annual data ranging from 2000 to 2023. Second-generation panel unit root and cointegration tests are used because of the cross-sectional dependence between our considered variables. The cross-sectional distributed lag (CS-DL) methodology is performed to estimate our long-run coefficients. Several novel results are highlighted. In the long-run, arms imports increase political stability and economic growth. While military expenditures increase oil exports, arms imports slightly reduce them. Oil exports increase military expenditures but reduce arms imports. Political stability reduces military expenditures and increases gross domestic product. These oil-exporting Gulf countries are advised to reinforce their military efforts, in particular by planning the production of high-tech weapons, to improve their oil exports and thus their gross domestic product. Economic growth combined with political stability enables them to become producing and exporting renewable energy countries through adequate energy efficiency and renewable energy strategies. Jel classification: C33; H56; O53 ; Q37.
Yasir Rafique, Jue Wu, Abdul Wahab Muzaffar
et al.
Industrial organizations are turning to recommender systems (RSs) to provide more personalized experiences to customers. This technology provides an efficient solution to the over-choice problem by quickly combing through large amounts of information and supplying recommendations that fit each user’s individual preferences. It is quickly becoming an integral part of operations, as it yields successful and convenient results. This research provides an enhanced integrated fuzzy logic-based deep learning technique (EIFL-DL) for recent industrial challenges. Extracting useful insights and making appropriate suggestions in industrial settings is difficult due to the fast development of data. Traditional RSs often struggle to handle the complexity and uncertainty inherent in industrial data. To address these limitations, we propose an EIFL-DL framework that combines fuzzy logic and deep learning techniques to enhance recommendation accuracy and interpretability. The EIFL-DL framework leverages fuzzy logic to handle uncertainty and vagueness in industrial data. Fuzzy logic enables the modelling of imprecise and uncertain information, and the system is able to capture nuanced relationships and make more accurate recommendations. Deep learning techniques, on the other hand, excel at extracting complex patterns and features from large-scale data. By integrating fuzzy logic with deep learning, the EIFL-DL framework harnesses the strengths of both approaches to overcome the limitations of traditional RSs. The proposed framework consists of three main stages: data preprocessing, feature extraction, and recommendation generation. In the data preprocessing stage, industrial data is cleaned, normalized, and transformed into fuzzy sets to handle uncertainty. The feature extraction stage employs deep learning techniques, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to extract meaningful features from the preprocessed data. Finally, the recommendation generation stage utilizes fuzzy logic-based rules and a hybrid recommendation algorithm to generate accurate and interpretable recommendations for industrial applications.
The social sciences and digital humanities have recently adopted the machine learning technique of topic modeling to address research questions in their fields. This is problematic in a number of ways, some of which have not received much attention in the debate yet. This paper adds epistemological concerns centering around the interface between topic modeling and linguistic concepts and the argumentative embedding of evidence obtained through topic modeling. It concludes that topic modeling in its present state of methodological integration does not meet the requirements of an independent research method. It operates from relevantly unrealistic assumptions, is non-deterministic, cannot effectively be validated against a reasonable number of competing models, does not lock into a well-defined linguistic interface, and does not scholarly model topics in the sense of themes or content. These features are intrinsic and make the interpretation of its results prone to apophenia (the human tendency to perceive random sets of elements as meaningful patterns) and confirmation bias (the human tendency to perceptually prefer patterns that are in alignment with pre-existing biases). While partial validation of the statistical model is possible, a conceptual validation would require an extended triangulation with other methods and human ratings, and clarification of whether statistical distinctivity of lexical co-occurrence correlates with conceputal topics in any reliable way.
History of scholarship and learning. The humanities, Bibliography. Library science. Information resources
Eva Pfanzelter, Sarah Oberbichler, Jani Marjanen
et al.
Many libraries offer free access to digitised historical newspapers via user interfaces. After an initial period of search and filter options as the only features, the availability of more advanced tools and the desire for more options among users has ushered in a period of interface development. However, this raises a number of open questions and challenges. For example, how can we provide interfaces for different user groups? What tools should be available on interfaces and how can we avoid too much complexity? What tools are helpful and how can we improve usability? This paper will not provide definite answers to these questions, but it gives an insight into the difficulties, challenges and risks of using interfaces to investigate historical newspapers. More importantly, it provides ideas and recommendations for the improvement of user interfaces and digital tools.
History of scholarship and learning. The humanities, Bibliography. Library science. Information resources
Eva Pfanzelter, Sarah Oberbichler, Jani Marjanen
et al.
International audience Many libraries offer free access to digitised historical newspapers via user interfaces. After an initial period of search and filter options as the only features, the availability of more advanced tools and the desire for more options among users has ushered in a period of interface development. However, this raises a number of open questions and challenges. For example, how can we provide interfaces for different user groups? What tools should be available on interfaces and how can we avoid too much complexity? What tools are helpful and how can we improve usability? This paper will not provide definite answers to these questions, but it gives an insight into the difficulties, challenges and risks of using interfaces to investigate historical newspapers. More importantly, it provides ideas and recommendations for the improvement of user interfaces and digital tools.
History of scholarship and learning. The humanities, Bibliography. Library science. Information resources
Collector's seals provide important clues about the ownership of a book. They contain much information pertaining to the essential elements of ancient materials and also show the details of possession, its relation to the book, the identity of the collectors and their social status and wealth, amongst others. Asian collectors have typically used artistic ancient characters rather than modern ones to make their seals. In addition to the owner's name, several other words are used to express more profound meanings. A system that automatically recognizes these characters can help enthusiasts and professionals better understand the background information of these seals. However, there is a lack of training data and labelled images, as samples of some seals are scarce and most of them are degraded images. It is necessary to find new ways to make full use of such scarce data. While these data are available online, they do not contain information on the characters' position. The goal of this research is to assist in obtaining more labelled data through user interaction and provide retrieval tools that use only standard character typefaces extracted from font files. In this paper, a character segmentation method is proposed to predict the candidate characters' area without any labelled training data that contain character coordinate information. A retrieval-based recognition system that focuses on a single character is also proposed to support seal retrieval and matching. The experimental results demonstrate that the proposed character segmentation method performs well on Asian collector's seals, with 85% of the test data being correctly segmented.
History of scholarship and learning. The humanities, Bibliography. Library science. Information resources
Collector's seals provide important clues about the ownership of a book. They contain much information pertaining to the essential elements of ancient materials and also show the details of possession, its relation to the book, the identity of the collectors and their social status and wealth, amongst others. Asian collectors have typically used artistic ancient characters rather than modern ones to make their seals. In addition to the owner's name, several other words are used to express more profound meanings. A system that automatically recognizes these characters can help enthusiasts and professionals better understand the background information of these seals. However, there is a lack of training data and labelled images, as samples of some seals are scarce and most of them are degraded images. It is necessary to find new ways to make full use of such scarce data. While these data are available online, they do not contain information on the characters' position. The goal of this research is to assist in obtaining more labelled data through user interaction and provide retrieval tools that use only standard character typefaces extracted from font files. In this paper, a character segmentation method is proposed to predict the candidate characters' area without any labelled training data that contain character coordinate information. A retrieval-based recognition system that focuses on a single character is also proposed to support seal retrieval and matching. The experimental results demonstrate that the proposed character segmentation method performs well on Asian collector's seals, with 85% of the test data being correctly segmented.
History of scholarship and learning. The humanities, Bibliography. Library science. Information resources
Abstract Merging the citation counts of arXiv-deposited e-prints (arXiv version) with those of their corresponding published journal articles (publisher version) is an important issue in citation analysis. Using examples of arXiv-deposited e-prints, this article adopts a manual approach to investigate the processing methods used by bibliographic repositories such as Google Scholar, Web of Science, Scopus, Astrophysics Data System (ADS), and INSPIRE for the citation merging. Both Google Scholar and ADS consolidate all citations from the two versions into the publisher one, whereas the consolidated citations are accumulated into the arXiv version in the INSPIRE repository. All these methods ignore the categories of the arXiv-deposited versions and the corresponding availability dates. As for Web of Science and Scopus, they count the citations of the two versions separately, which is likely regarding them as two independent articles. Focusing on journal articles that also appeared as arXiv e-prints, we classify them into two categories and identify two public availability dates of articles as the starting point of citation statistics. We present four feasible schemes to consolidate citation counts for the articles with both versions and also propose a universal scheme based on the research output. Furthermore, we investigated 2,662 e-prints in the “Computer Science - Digital Libraries” subject (cs.DL) from 1998 to 2018 in arXiv.org and manually calculated the consolidated citation counts of arXiv-deposited articles with the corresponding citation merging schemes. Furthermore, these citation consolidation methods are applied to the evaluation of articles, authors, and journals. Such empirical testing proves the feasibility of the schemes proposed in this article.
The creation of the Artist Libraries Project was sparked by the observation that artist libraries are still not well known, yet many art historians are interested in this archive for the value it adds to understanding the person behind the artist and his or her creative process. The problem is that these libraries are rarely physically preserved. To remedy this dispersion, we built an online database and a website www.lesbibliothequesdartistes.org that house this valuable source in the form of lists of books and their electronic versions. First data on Monet's library have been made available, and several additional artist libraries from the 19 th and 20 th centuries are on the way for 2019. By gathering all these bibliographical data in a central database, it's possible to explore one library and to compare several. This article explains how we built the database and the website and how the implementation of those IT tools has raised questions about the use of this resource as an archive on the one hand, as well as its value for art history on the other.
History of scholarship and learning. The humanities, Bibliography. Library science. Information resources
The creation of the Artist Libraries Project was sparked by the observation that artist libraries are still not well known, yet many art historians are interested in this archive for the value it adds to understanding the person behind the artist and his or her creative process. The problem is that these libraries are rarely physically preserved. To remedy this dispersion, we built an online database and a website www.lesbibliothequesdartistes.org that house this valuable source in the form of lists of books and their electronic versions. First data on Monet's library have been made available, and several additional artist libraries from the 19 th and 20 th centuries are on the way for 2019. By gathering all these bibliographical data in a central database, it's possible to explore one library and to compare several. This article explains how we built the database and the website and how the implementation of those IT tools has raised questions about the use of this resource as an archive on the one hand, as well as its value for art history on the other.
History of scholarship and learning. The humanities, Bibliography. Library science. Information resources
This paper is a reply to the article "Scopus's Source Normalized Impact per Paper (SNIP) versus a Journal Impact Factor based on Fractional Counting of Citations", published by Loet Leydesdorff and Tobias Opthof (arXiv:1004.3580v2 [cs.DL]). It clarifies the relationship between SNIP and Elsevier's Scopus. Since Leydesdorff and Opthof's description of SNIP is not complete, it indicates four key differences between SNIP and the indicator proposed by the two authors, and argues why the former is more valid than the latter. Nevertheless, the idea of fractional citation counting deserves further exploration. The paper discusses difficulties that arise if one attempts to apply this principle at the level of individual (citing) papers.