The purpose of this study was to investigate the of metadata elements of Digital Rights Management (DRM) comparatively in different regions and the approach behind. This research was conducted using qualitative content analysis method. The data was gathered through documentary method and searching in databases to identify the best practices of DRM solutions. The results of this study revealed that, different metadata elements are utilized in DRM projects. When it comes to copyright, the US tends to be more pro-owner, while the Canada and UK prefers a balanced perspective that includes user activities. France and Germany have adopted strict measures in this respect, having legal provisions for sanctioning offenders. Switzerland has a more relaxed approach to DRM systems, while Australia, China, and Russia have a complex legal framework for legal protection, access controls, permissions of copyrighted content. It can be stated that, Metadata is an essential component in developing DRM systems. Rights metadata have various functionalities such as Identifying and describing the content, to manage secure content distribution, access control, content protection, and usage tracking, monitoring changes, facilitate discoverability, within DRM systems the extent to which they protected content remains secure and accessible only to authorized users. In conclusion, it could be said that based on context-based approaches, cultural norms, and infrastructures there is significant differences in approaches to the protection of digital content and this affect the types and functionalities of right metadata elements in the DRM systems.

Improving participation in voluntary activities in Iran is important because increasing productivity among young people, given the country's young population, contributes to community sustainability. Therefore, a better understanding of volunteer motivation in Iranian youth is needed. The Volunteer Functions Inventory (VFI) for assessing volunteer motivations has good psychometric properties and is adapted to several languages, but no validated Iranian translation yet exists. The purpose of this study was to investigate the psychometric Characteristics of voluntary functions inventory in members of Iranian Red Crescent Society. Sample size was 595 members of Youth Organization of Iranian Red Crescent Society from 31 provinces and 175 cities of Iran that were selected by multi-stage cluster sampling method and responded to voluntary functions inventory. Data were collected using a demographic sample and voluntary functions inventory (VFI). Confirmatory factor analysis using principal components method was used for data analysis. The results of the present study showed that the voluntary functions inventory had validity and reliability. Also, the factor structure showed that 29 items and 6 factors well assess people's attitudes to volunteering, and the structure of this inventory was well-fitted and confirmed all goodness of fit models. The present study provides the use of the Iranian translation of the Voluntary Functions Inventory (6 scales and 29 items) to assess volunteer motivation among young Iranian volunteers.

Nowadays, standardized metadata for geospatial data is a key in sharing and finding information on the web and crucial in building Geospatial Data Infrastructure (GDI). The main objective of this paper was to develop a web-based metadata dissemination system for in-situ sensors based on, most importantly, interoperable, standard and open technologies introduced by Open GIS Consortium (OGC), namely Geography Markup Language (GML). In this research, at first a use case diagram was developed to demonstrate the user’s requirement. Then, an application XML schema based on user’s requirement was created. To build this schema, some GML schema documents (developed by Open GIS Consortium (OGC)) were imported into the application schema. System architecture was designed based on client/server model and a UML class diagram was also developed to present all classes and their attributes, operations and associations within the system. Implementation was conducted using GML, XML, XMLHTTP, DOM, ASP, and VBScript that brought out a web-network-based in-situ sensors metadata application. This application provided a user friendly interface to search and find sensor related information. Results showed that although GML and XML are powerful tools to build geo-metadata, it is important to note that GML document size may be a problem when dealing with huge amount of data.

In this paper, an alternative approach in operational modal analysis is presented, utilizing image processing technique and transmissibility functions. Imaging sensors do not impose additional mass on the structure due to their non-contact nature, while transmissibility functions, independent of excitation type, can directly extract mode shapes. The innovation of this research lies in combining these two techniques to record dynamic responses and identify modal properties. To capture the temporal response history from video signals, the block-matching method with sub-pixel accuracy was employed. Validation was conducted by recording the response of the tip of a cantilevered steel beam subjected to impact excitation, using a high-speed camera and a laser vibrometer, simultaneously. The RMSE plots in the time domain and the PSD in the frequency domain indicate high accuracy of this method. Using this approach, the displacement time histories of various points on the structure were extracted from the video signals, and the modal properties, including natural frequencies, damping ratios, and mode shapes, were identified using the transmissibility matrix method. The results obtained from the proposed method were compared with the stochastic subspace identification (SSI) method and analytical solutions. The findings reveal the accuracy of the modal identification approach introduced in this article. The highest relative error in estimating the natural frequencies of the first and second modes, compared to the values from the laser method, are 0.19% and 0.13%, respectively, and in comparison to the analytical values, they are 0.34% and 1.5%, respectively.

Purpose: Designing metadata ontology model for semantic representation of Theses by using the SPAR (Semantic Publishing and Referencing) Ontologies.Method: This study was an applied form and two methods were used, Content Analysis and mapping. The metadata of 69 theses and dissertations on the National Library and Archive of Iran in three Databases: 1) Digital Library of National Library and Archive of Iran. 2) Rasa Software and 3) Ganj in the Iranian Research Institute for Information Science and Technology were selected modified and completed by mapping. On the other hand, by analyzing the entities of each SPAR ontology and suggesting another entity to the researcher, the checklist was formed. This checklist included classes, properties, and individuals. At last, by entering them into Protégé software version 5.5, the model of metadata ontology, MdOntTDs, was drawn.Findings: Findings identified deficiencies in the existence of four important metadata elements (subject, supervisor, advisor, and abstract) in RASA and NLAI Digital Library. Among the 18 SPAR Ontologies, the most entities were selected from FaBiO, FRAPO, and CiTO respectively. All entities of BiDO, BiRO, C4O, Fivestar, FR, FRBR, PO, PRO, PSO, and PWO were suitable for theses. 195 individuals from 6 SPAR Ontologies, 292 individuals labeled with MdTDs from theses, and 100 individuals labeled with SUNMdTDs were selected by the researcher and entered into the software. 1558 entities categorized by class, Properties (object, data, and Annotation), and individuals along with the description and definition of each entity were placed in the software, in the form of hierarchical and determining axioms for classes. And specifying domain and range for relationships. Finally, the RDF graph was drawn using the OntoGraf plugin, and the final Model, MdOntTDs was developed. this research has proposed three new types of metadata: 1) Except for the existing keywords, topics have been categorized and modeled up to three levels including 4 main categories, 16 subcategories, and many units. Each of these final topics has been related to “hasSubject” and “isSubjectOf” properties. 2) The research methods of Theses that were connected with “hasMethod” and “used in” properties. 3) The papers taken from Theses were also searched, as far as possible, and were connected with “hasJournalArticle” and “journalArticleOf” properties.Conclusion: This model, if implemented, can overcome keyword search limitations, the problem of linking and Data sharing on the web, and the inconsistency of data. In the software, classes and their related individuals are visible in the form of a hierarchical network in RDF triples, and the connection between entities with increasing access points promises deeper semantic searches. However, due to the absence or lack of tagged and linked data, usage of the some of selected entities is not possible.

Purpose: This research aimed to evaluate and validate the metadata of learning objects in organizational repositories of Iranian medical sciences universities based on the standard of learning object metadata.Method: This research was conducted with a thorough approach, utilizing observation and survey methods. We identified sixteen repositories related to Iranian universities of medical sciences. The metadata elements of learning objects and the standards used in organizing electronic learning objects in these repositories were meticulously identified. The elements from the electronic learning objects of the institutional repositories of Iranian medical sciences universities were then matched with the checklist of standard learning object metadata elements, and their overlap was determined to describe the electronic learning objects in the organizational repositories. The next part of the research involved the implementation of the Delphi technique and the validation of the metadata elements of the learning objects in the organizational repositories of the universities of medical sciences in Iran. A questionnaire was designed for the statistical community, which included specialists in the field of information organization and specialists in the field of e-learning, and was sent out in two rounds.Findings: The findings showed that many of the standard metadata elements of the learning object are not covered, and out of the 60 standard metadata elements of the learning object, 25 elements (41%) are covered. Metadata elements related to the life cycle characteristics of electronic learning objects had the highest degree of matching (66%). In comparison, elements related to the genera category of learning objects with six items (60%) of 10 features had the second highest degree of matching. The compliance rate is zero in the Annotation category of the metadata standard of the learning object. The degree of compliance is reported for one item for the description of metadata and the rights of learning objects. The findings from the Delphi rounds showed that in determining the importance of metadata elements for describing e-learning objects, which was designed with a Likert scale (very large to very low), the favourable result was about the presence of metadata elements in the organization. The storage of electronic learning objects in the institutional repositories of Iranian medical sciences universities was obtained with 89.73% frequency. The findings from the first and second rounds of Delphi about determining the correspondence of the metadata elements of the description of electronic learning objects with the standard metadata elements of the learning object showed that 97.24% had the highest correspondence.Conclusion: The potential impact of this research is significant. The findings suggest that in creating metadata schemas and guidelines, it is crucial to ensure their compliance with the chosen standard. The learning object metadata standard, with its breadth, comprehensiveness, and acceptability, emerges as a suitable standard for organizing electronic learning objects in the organizational repositories of Iran's universities of medical sciences. The evaluation of the questionnaire revealed that a limited percentage of experts disagreed with the presented items. However, the evaluators largely agreed with the mentioned items, enhancing the credibility and potential impact of the research.

In today's world, social networks that have become a part of people's daily life, including Twitter, Telegram, Instagram, etc., are increasing and expanding day by day. Therefore, the number of their users is also increasing and as a result, a large amount of data is being exchanged and stored in these network; and this huge amount of data has turned social networks, especially Twitter, into big data. It is very important to manage, organize and prune these big data, as well as to predict the behavior of social network users. One of the most important and effective methods for predicting user relationships in social networks is classification techniques, which in most of the applications and researches in the background of the research, are still based on criteria such as ‘accuracy; and accuracy of prediction. have weakness In this article, in order to predict the user relationship in Twitter social networks, the cumulative classification method based on voting, which has two basic steps, has been used. In the first step, by using basic classification algorithms including nearest neighbor, decision tree, random forest and simple Bayesian, the outputs of each classification are obtained. In the second step, the final output of cumulative classification is calculated using the voting method. The results of the experiments on the dataset of the Twitter social network and based on the criteria of accuracy, correctness and coverage, argue that the proposed cumulative classification method based on voting has more favorable results than It has other algorithms      

Purpose: This paper examines and compares compliance of seven software, namely Calm for Archives Version 9. 3, Collective Access Version 1. 7, Archives Space Version 2. 4. 1, Archivematica Version 1. 8, Adlib XPlus Version 2, Cuadra Star Single version and Eloquent Archives Single version with the existing archival standards. Methodology and Research Design: A researcher deigned checklist consisting of 9 main and 62 sub-sections was used to record 272 features of the archival software, then compared against existing standards and with each other. Findings and Conclusion: Significancant differences were noticed. Calm for Archives, Collective Access, Archives Space, Archivematica, Adlib XPlus, Cuadra Star, Eloquent Archives are (p-value) <0. 05. In addition, the chi-square was larger than the critical table χ 2 with df = 1. Most features and capabilities respectively are archival softwares: Archives Space 54%, Adlib XPlus 39%, Eloquent Archives 37%, Calm for Archives 29%, Collective Access 28%, Archivematica 27%, and Cuadra Star 26%. With respect to the support of metadata standards, Archives Space, Cuadra Star, Eloquent Archives, Archivematica, Collective Access, Calm for Archives, and Adlib XPlus will be archiving, and in support of archival standards, respectively, Archives Space, Eloquent Archives, Adlib XPlus, Cuadra Star, Calm for Archives, Collective Access and Archivematica. Regarding the support of the exchange protocols, Archives Space earned the first position and Adlib XPlus, ranked second, while the rest of the softwares were similar.