Multimedia Database Research Articles

Legendary fermented herbs: an ethnobotanical study of the traditional fermentation starter of the Chuanqing people in Northwestern Guizhou, China

BackgroundPlants that contain brewing microorganisms are used in traditional fermentation starters, which are an essential part of local diet, nutrition, life, and health. Regionally, the plant species used and the microorganisms included in traditional fermentation starters are diverse, endowing local fermented drinks with different flavors and health benefits. However, related traditional knowledge has been scarcely documented or revealed.MethodsAn ethnobotanical survey was conducted in five towns of Nayong County in northwestern Guizhou, China. Snowball sampling, semi-structured interviews, free lists, and participatory observation were used to collect information on Jiuqu Plants (JPs) and jiuqu-making techniques. The PacBio platform was used to study the microbial community structure and diversity in the Chuanqing people’s jiuqu.ResultsIn total, 225 informants were interviewed, including 116 who provided plants and technological processes for making Chinese baijiu jiuqu (CBJ) and 139 who provided information about making fermented glutinous rice jiuqu (FGRJ). This study found that older people have more abundant knowledge about CBJ plants. Poaceae was found to be the dominant family used in making CBJ and FGRJ (7 species each). Compared to individual plant parts, the whole plant is most commonly used in two kinds of jiuqu (19.5% in CBJ and 22.6% in FGRJ). The Chuanqing people’s jiuqu is used to treat dietary stagnation and indigestion. The highest relative frequency of citation of the CBJ plant was Ficus tikoua Bureau, and the counterpart of the FGRJ plant was Buddleja macrostachya Benth. The dominant bacterial species in jiuqu were Gluconobacter japonicus (YQ1, YQ4) and Pediococcus pentosaceus (YQ2, YQ3), and the dominant fungal species was Rhizopus oryzae.ConclusionFor the first time, this study documents the unique traditional jiuqu knowledge and reveals the microbial mystery behind the FGRJ of the Chuanqing people.Therefore, this study encourages the use of online social media platforms in order to spread Jiuqu culture, the use of the new media wave in order to create multimedia databases, and also suggests that local communities should develop preservation intervention programs, in addition to nurturing the inheritors in order to prevent the disappearance of traditional Jiuqu knowledge. This research contributes to the conservation and demystification of the traditional jiuqu knowledge of the Chuanqing people and lays the foundation for further research on its microbiology, nutrition, and metabolomics.

Evaluation Method of Intelligent Teaching in Physical Training Classrooms Based on Multimedia Information Retrieval Technology

In different historical periods, people have different demands for Physical Education (PE), and the educational goal of school PE will also change, and the teaching mode and requirements of school PE will also be different. Multimedia information retrieval (IR) technology refers to searching in a large-scale multimedia database according to the content and context of media and media objects. In this paper, the Back Propagation instructional level of physical training class, and model is established. The BPNN is used to analyze the Multimedia IR data, and the simulation and experiment show the effectiveness of the assessment model, which provides a new method for comprehensively, fairly and scientifically evaluating the teaching work. This method is improved by 11.85% compared with the comparative assessment algorithms. The method of using BPNN to evaluate instructional level is easy to operate, which can overcome the shortcomings of traditional assessment methods, and avoid the complicated process of traditional assessment of instructional level.

Guidelines to support the design, and selection and appraisal of multimedia teaching aids for microbiology education.

Microbiology education has a serious handicap - the lack of visibility of the players of the subject and their interactions - which engenders a disproportionate reliance upon multimedia teaching aids (MTAs). The International Microbiology Literacy Initiative (IMiLI) is creating educational resources in societally-relevant microbiology complemented by appropriate MTAs. However, proper guidance supporting microbiology educators in locating and selecting, or commissioning the creation of, adequate MTAs for different target audiences and learning objectives is lacking. The aims of this study were to (i) identify important considerations regarding educational/didactical standards and the design of educational multimedia and (ii) create an evidence-based guideline for selecting and appraising existing, and informing the creation of new, microbiology MTAs. This investigation is based on an exploratory, mixed-methods approach. The results of two literature reviews (covering educational and good practice multimedia design) informed the collation of a preliminary appraisal guideline for videos, animations, comics, and video games. A web-scraping approach was utilised to locate and retrieve existing exemplars of the four multimedia types and create four pertinent multimedia databases (including metadata). The preliminary guideline was piloted (and revised accordingly) by appraising quasi-random (or purposive) samples of each multimedia type. Educational multimedia experts were interviewed to discuss the findings. Finally, the guideline was updated to reflect the expert comments together with the results of the pilot appraisals. The final guideline has four components: (i) central considerations for selecting and appraising multimedia for specific audiences and educational purposes, (ii) multimedia selection tool, (iii) multimedia appraisal tools, and (iv) extensive background information as appendices linking all sections for further comprehension. Broad utilisation of the guideline has significant potential for simplifying and systematising multimedia selection/creation, leading to superior multimedia-based learning outcomes, establishing a rapid selection database (pre-appraised multimedia), reducing disparities in microbiology education and incentivising educational content creators.

Retracted: Security Risk and Preventive Measures of Multimedia Database System under Remote Control of Network Robot

Retracted: Security Risk and Preventive Measures of Multimedia Database System under Remote Control of Network Robot

Retracted: On the Design of Assistant Teaching Using Network Multimedia Database in Volleyball Teaching

Retracted: On the Design of Assistant Teaching Using Network Multimedia Database in Volleyball Teaching

Dynamic Hybrid Fragmentation Method for Multimedia Databases

Multimedia databases store high-volume data, which causes problems in efficient information retrieval, and increases execution costs and response times of the queries. To solve this problem, data fragmentation techniques exist to improve query performance, increase information availability, and efficiently execute more operations accessing less irrelevant data. This article presents a comprehensive review of 34 methods related to hybrid fragmentation and subsequently proposes the design of a hybrid fragmentation method that adapts the scheme according to workload changes to maintain efficient retrieval of multimedia data. The proposed technologies are Java as a programming language, Java Server Faces (JSF) as a framework, MySQL and MongoDB database management systems, and NetBeans as an Integrated Development Environment (IDE), following the UWE methodology (Unified Modeling Language-based Web Engineering).

Deep Learning for Approximate Nearest Neighbour Search: A Survey and Future Directions

Approximate nearest neighbour search (ANNS) in high-dimensional space is an essential and fundamental operation in many applications from many domains such as multimedia database, information retrieval and computer vision. With the rapidly growing volume of data and the dramatically increasing demands of users, traditional heuristic-based ANNS solutions have been facing great challenges in terms of both efficiency and accuracy. Inspired by the recent successes of deep learning in many fields, substantial efforts have been devoted to applying deep learning techniques to ANNS for learning to index and learning to search, resulting in numerous algorithms that achieve state-of-the-art performance compared with conventional methods. In this survey paper, we comprehensively review the different types of deep learning-based ANNS methods according to two learning paradigms: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">learning to index</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">learning to search</i> . We provide a comprehensive overview and analysis of these methods in a systematic manner. Based on the overview, we point out that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">end-to-end learning</i> will be a new and promising research direction for deep learning-based ANNS, i.e., applying deep learning techniques to jointly learn the indexing and searching together, such that the underlying knowledge learned from data can directly contribute to the final searching performance. Finally, we conduct experiments and provide general performance analyses for the representative deep learning-based ANNS algorithms.

CONTENT BASED IMAGE RETRIVAL USING DIFFERENT CLUSTERING TECHNIQUES

CBIR (Content based image retrieval) is the software system for retrieving the images from the database by using their features. In CBIR technique, the images are retrieved from the dataset by using the features like color, text, shape,texture and similarity. Object recognition technique is used in CBIR. Research on multimedia systems and content-based image retrieval is given tremendous importance during the last decade. The reason behind this is the fact that multimedia databases handle text, audio, video and image information, which are of prime interest in web and other high end user applications. Content-based Image retrieval deals with the extraction of knowledge, image data relationship, or other patternsnot expressly keep within the pictures. It uses ways from computer vision, image processing, image retrieval, data retrieval, machine learning, database and artificial intelligence. Rule retrieval has been applied to large image databases. The proposedsystem gives average accuracy of 90%. Keywords— CBIR, Color feature, Shape feature, Texture feature, Feature extraction, Clustering, Image Retrieval.

Security Risk and Preventive Measures of Multimedia Database System under Remote Control of Network Robot

The rapid development of network technology makes the world enter a new era, but it also brings a variety of severe information security problems, which makes the network security more and more important. Based on the existing literature and information, this paper expounds the current situation of database information system security. In view of the security risks of the media database information, this paper proposes to use the remote control system of the network robot, through sorting out the organizational structure characteristics and technology of multimedia data, establish the security defense system, and try to manage the multimedia data security. This system takes the mobile robot as the control object and adds the vision and ultrasonic transducer for the robot, so that it can carry on the semi-autonomous movement under the control of human. In addition, the host PC is used as the main control terminal to send instructions to the remote robot and receive the feedback data information. The simulation results show that the robot remote control system has good security, can ensure the establishment of database security defense technology system, and has the characteristics of convenient operation, easy to expand, and strong mobility. From the research point of view of this paper, the combination of robotics and multimedia information security is booming and will become a new application prospect.

The discourse uses of the verb dire ‘to say’ in Vernacular French: A corpus-based exploration

This article provides a descriptive account of the major uses of the speech verb dire “to say” in Vernacular French. CLAPI Corpus (Corpus de Langue Parlée en Interaction), which is a multimedia database of corpora recorded in real situations (i.e. professional, institutional, commercial, didactic, and medical) is used. Five major uses of the verb dire are found, namely quotative (speech) dire, epistemic dire¸ evocative dire, desiderative dire, and copular dire. Unlike quotative dire, epistemic dire, evocative dire, desiderative dire and copular dire are restricted in terms of their occurrences (with varying degrees between them). For instance, the verb dire under some of these uses does not take place in the perfect tense, while under other uses it is only restricted to a specific type of subjects (i.e. the demonstrative pronoun ça). We take these restrictions as evidence that this verb undergoes different stages of grammaticalization. Therefore, the study concludes that the verb dire is a target of a grammaticalization process that causes the semantic shift that the verb dire in Spoken French witnesses.

Artificial intelligence in media: Perspectives and implications

With the explosive growth of information on the web, users face difficulties finding their desired information. There is a need to manage and cluster data efficiently. Although there are various multimedia database systems available for retrieval, most of the methods are not efficient enough. Artificial Intelligence (AI) is increasingly shaping media production and consumption, particularly in the field of video blogs (vlogs). This paper explores the intersection of AI and media, focusing on its implications for freedom of speech and media, content creation, video recommendations, content moderation, and content personalization. The objective is to extract relevant videos from a multimedia database, evaluate the performance of AI algorithms in processing video data, and demonstrate the effectiveness of these algorithms in enhancing the quality and accessibility of video blogs.

Random Online Hashing for Cross-Modal Retrieval.

In the past decades, supervised cross-modal hashing methods have attracted considerable attentions due to their high searching efficiency on large-scale multimedia databases. Many of these methods leverage semantic correlations among heterogeneous modalities by constructing a similarity matrix or building a common semantic space with the collective matrix factorization method. However, the similarity matrix may sacrifice the scalability and cannot preserve more semantic information into hash codes in the existing methods. Meanwhile, the matrix factorization methods cannot embed the main modality-specific information into hash codes. To address these issues, we propose a novel supervised cross-modal hashing method called random online hashing (ROH) in this article. ROH proposes a linear bridging strategy to simplify the pair-wise similarities factorization problem into a linear optimization one. Specifically, a bridging matrix is introduced to establish a bidirectional linear relation between hash codes and labels, which preserves more semantic similarities into hash codes and significantly reduces the semantic distances between hash codes of samples with similar labels. Additionally, a novel maximum eigenvalue direction (MED) embedding method is proposed to identify the direction of maximum eigenvalue for the original features and preserve critical information into modality-specific hash codes. Eventually, to handle real-time data dynamically, an online structure is adopted to solve the problem of dealing with new arrival data chunks without considering pairwise constraints. Extensive experimental results on three benchmark datasets demonstrate that the proposed ROH outperforms several state-of-the-art cross-modal hashing methods.

A szótagzáró lvariabilitása szlovákiai magyar nyelvjárási hangoskönyvek szövegeiben

With the help of the dialectological software Bihalbocs, regional dialect texts combined with sound were published under the title Hungarian Dialectal Talking Book. The collection, which has become a series, currently comprises 16 parts. The advantage of the software is that the texts are linked to the audio files, i.e. it synchronizes them to the millisecond. By clicking anywhere in the text, we can listen to the dialect data and any part of the text at any time, without having to look up the original file and search for the desired part. This technique was used to create the Slovakia Hungarian Dialectal Talking Book I-III. which publishes dialect texts from the 3 main areas of Hungarian dialect regions extending into Slovakia (the Central Transdanubian – Little Hungarian Plain dialect, the Palóc dialect and the Northeastern dialect). The paper firstly recounts the design and creation of this multimedia database, followed by a brief description of certain parts as well as the structure of the audiobooks. The next part of the study discusses the mapping possibilities based on the quantitative analysis of the audiobooks. Such computational dialectological studies tend to employ two different methods: firstly, using the automated search function without any prior grouping by the researchers, and secondly, using the search function once the data is annotated. Computational methods not only reduce the amount of effort required but also provide plenty of opportunities for more granulated dialectological analyses. The quantitative methods applied concentrate on the distribution of certain phenomena affecting the system, prevalence, and realization of phonemes. The paper describes the regional characteristics for each of these phenomena based on data from the audiobooks. The study analyzes the presence, omission, and reduction of syllable-final l in 34 dialect texts at 27 research points, depending on the phonological situation and the duration of the vowel before l. This paper presents the maps created with the Bihalbocs program to illustrate the regional variability of syllable-final l based on the analyzed regional Hungarian dialect texts in Slovakia.

Average Approximate Hashing-Based Double Projections Learning for Cross-Modal Retrieval.

Cross-modal retrieval has attracted considerable attention for searching in large-scale multimedia databases because of its efficiency and effectiveness. As a powerful tool of data analysis, matrix factorization is commonly used to learn hash codes for cross-modal retrieval, but there are still many shortcomings. First, most of these methods only focus on preserving locality of data but they ignore other factors such as preserving reconstruction residual of data during matrix factorization. Second, the energy loss of data is not considered when the data of cross-modal are projected into a common semantic space. Third, the data of cross-modal are directly projected into a unified semantic space which is not reasonable since the data from different modalities have different properties. This article proposes a novel method called average approximate hashing (AAH) to address these problems by: 1) integrating the locality and residual preservation into a graph embedding framework by using the label information; 2) projecting data from different modalities into different semantic spaces and then making the two spaces approximate to each other so that a unified hash code can be obtained; and 3) introducing a principal component analysis (PCA)-like projection matrix into the graph embedding framework to guarantee that the projected data can preserve the main energy of data. AAH obtains the final hash codes by using an average approximate strategy, that is, using the mean of projected data of different modalities as the hash codes. Experiments on standard databases show that the proposed AAH outperforms several state-of-the-art cross-modal hashing methods.

First saying and second saying in aphasic conversations

Objective: This present study investigates first and second saying in aphasic conversations to demonstrate the ability of qualitative methodologies (in this case conversation analysis) to study the ways in which persons with aphasia achieve conversation success through verbal repetition in the form of first and second sayings. Method: For this explorative case study, the author drew on data from AphasiaBank, a multimedia database of discourse samples gathered from individuals with aphasia and from healthy controls. Using the framework of conversation analysis, the author discusses its position, composition, and action. Results: We demonstrated the role of the practice of recycling elements of one’s own prior utterances in building socially meaningful action, presenting an image of the speaker with aphasia as someone who is competently and confidently managing throughout her impairment. Discussion: The author discusses the potential of conversation analytical techniques as tools to study the complex phenomenon of conversation as the primary vehicle for human social action. Conclusion: Through the study of ‘first saying and second saying’ in aphasic conversation, this study contributes to our understanding of how persons with aphasia strategically employ their limited linguistic resources to negotiate meaning and social action.

On the Design of Assistant Teaching Using Network Multimedia Database in Volleyball Teaching

Physical education is an important part of school’s physical education and practical teaching activity. There are many restricting factors in physical education, such as the type of equipment and environmental conditions. The standardization of volleyball teaching technology has become the primary factor affecting teaching efficiency. Teachers demonstrate that the action is not standard and will lead students to learn that the technical action is not in place, and teachers can show students standardized technical action through multimedia technology, for example, through the video of athletes. The spatiotemporal nature presented in volleyball technology teaching affects students’ understanding and mastering of technology, using network multimedia system-assisted volleyball training teaching, using the advantages of network multimedia, volleyball teaching students difficult to understand the technical action of the intuitive display, improve students’ independent learning ability. This thesis studies the application of multimedia technology in the training and teaching of physical volleyball in colleges and universities. It analyzes the application of multimedia technology in the training and teaching of physical volleyball in colleges and universities, so as to provide useful references for the teaching reform of physical volleyball in colleges and universities.

Interstitial lung disease detection using template matching combined sparse coding and blended multi class support vector machine.

Interstitial lung disease (ILD), representing a collection of disorders, is considered to be the deadliest one, which increases the mortality rate of humans. In this paper, an automated scheme for detection and classification of ILD patterns is presented, which eliminates low inter-class feature variation and high intra-class feature variation in patterns, caused by translation and illumination effects. A novel and efficient feature extraction method named Template-Matching Combined Sparse Coding (TMCSC) is proposed, which extracts features invariant to translation and illumination effects, from defined regions of interest (ROI) within lung parenchyma. The translated image patch is compared with all possible templates of the image using template matching process. The corresponding sparse matrix for the set of translated image patches and their nearest template is obtained by minimizing the objective function of the similarity matrix of translated image patch and the template. A novel Blended-Multi Class Support Vector Machine (B-MCSVM) is designed for tackling high-intra class feature variation problems, which provides improved classification accuracy. Region of interests (ROIs) of five lung tissue patterns (healthy, emphysema, ground glass, micronodule, and fibrosis) selected from an internal multimedia database that contains high-resolution computed tomography (HRCT) image series are identified and utilized in this work. Performance of the proposed scheme outperforms most of the state-of-art multi-class classification algorithms.

Modified minimum spanning tree based vertical fragmentation, allocation and replication approach in distributed multimedia databases

Modified minimum spanning tree based vertical fragmentation, allocation and replication approach in distributed multimedia databases

Investigation of Relationships between Discrete and Dimensional Emotion Models in Affective Picture Databases Using Unsupervised Machine Learning

Digital documents created to evoke emotional responses are intentionally stored in special affective multimedia databases, along with metadata describing their semantics and emotional content. These databases are routinely used in multidisciplinary research on emotion, attention, and related phenomena. Affective dimensions and emotion norms are the most common emotion data models in the field of affective computing, but they are considered separable and not interchangeable. The goal of this study was to determine whether it is possible to statistically infer values of emotionally annotated pictures using the discrete emotion model when the values of the dimensional model are available and vice versa. A positive answer would greatly facilitate stimuli retrieval from affective multimedia databases and the integration of heterogeneous and differently structured affective data sources. In the experiment, we built a statistical model to describe dependencies between discrete and dimensional ratings using the affective picture databases NAPS and NAPS BE with standardized annotations for 1356 and 510 pictures, respectively. Our results show the following: (1) there is a statistically significant correlation between certain pairs of discrete and dimensional emotions in picture stimuli, and (2) robust transformation of picture ratings from the discrete emotion space to well-defined clusters in the dimensional space is possible for some discrete-dimensional emotion pairs. Based on our findings, we conclude that a feasible recommender system for affective dataset retrieval can be developed. The software tool developed for the experiment and the results are freely available for scientific and non-commercial purposes.

DIGITALISATION OF LIBRARIES (DIGITAL LIBRARIES) AND ITS SCOPE

In comparison to traditional libraries, digital libraries provide efficient and qualitative services by collecting, organizing, storing, disseminating, retrieving and preserving the information. Digital libraries support preservation besides making information retrieval and delivery more comfortable. It provides online access to historical and cultural documents whose existence is endangered due to physical decay. The major areas which offer digital libraries great exploitation are: Information retrieval, multimedia database, data mining, data warehouse, on-line information repositories, image processing, hypertext, World Wide Web and Wide Area Information Services (WAIS). Digital libraries necessarily include a strong focus on the management of digital content, just as traditional libraries have focused for long on the management of content in physical forms. Most of the digital content that is being managed includes human language, either in the form of character-coded electronic text, scanned versions of printed or handwritten text, or digital representations of human speech. Language technology therefore plays a major role in managing digital content. This comes as no surprise, of course. Digital libraries today make good use of what we know about searching large collections, and techniques such as machine-assisted indexing are employed increasingly often as we strive to extend our reach to progressively larger collections. But we are on the verge of a new era, one in which our machines will learn from what we do and then apply those capabilities to enable the management of digital content at a far larger scale than we could ever hope to do ourselves. Few advantages of digital libraries according to Haddouti are:User can access the information anywhere Reduces bureaucracy by providing access to the information The information is not necessarily located in same place Understanding the catalogue structure is not necessary Cross references to other documents speed up the work of users Full text search Protected information source Wide exploration and exploitation of the information The knowledge dissemination is an integral part of the success story of the popularity of creating digital libraries. The aim is to provide universal access to human knowledge, and given the advancement of digital storage and communications this goal is now achievable. KEY WORDS: Digitalization of Libraries, Role of community information centers in digitalization of libraries.