Search

The popularity of egocentric cameras and their always-on nature has lead to the abundance of day long first-person videos. The highly redundant nature of these videos and extreme camera-shakes make them difficult to watch from beginning to end. These videos require efficient summarization tools for consumption. However, traditional summarization techniques developed for static surveillance videos or highly curated sports videos and movies are either not suitable or simply do not scale for such hours long videos in the wild. On the other hand, specialized summarization techniques developed for egocentric videos limit their focus to important objects and people. This paper presents a novel unsupervised reinforcement learning framework to summarize egocentric videos both in terms of length and the content. The proposed framework facilitates incorporating various prior preferences such as faces, places, or scene diversity and interactive user choice in terms of including or excluding the particular type of content. This approach can also be adapted to generate summaries of various lengths, making it possible to view even 1-minute summaries of one's entire day. When using the facial saliency-based reward, we show that our approach generates summaries focusing on social interactions, similar to the current state-of-the-art (SOTA). The quantitative comparisons on the benchmark Disney dataset show that our method achieves significant improvement in Relaxed F-Score (RFS) (29.60 compared to 19.21 from SOTA), BLEU score (0.68 compared to 0.67 from SOTA), Average Human Ranking (AHR), and unique events covered. Finally, we show that our technique can be applied to summarize traditional, short, hand-held videos as well, where we improve the SOTA F-score on benchmark SumMe and TVSum datasets from 41.4 to 46.40 and 57.6 to 58.3 respectively. We also provide a Pytorch implementation and a web demo at https://pravin74.github.io/Int-sum/index.html.

Despite much research on the interdisciplinarity of the publications across subject categories, few studies analyze the interdisciplinarity of the technological knowledge flow among research entities (i.e., patent assignees, inventors, and countries). In this article, we propose a framework to identify the roles of the research entities by measuring the interdisciplinarity of the technological knowledge flow. Research entities are positioned on the two-dimensional maps based on the integration index, diffusion index, and specialization index, which are used to measure the degree of the interdisciplinarity of different research entities in knowledge flow. In order to explore the role of the research entities in knowledge flow, we put forward four kinds of research entities: diverse knowledge provider, active mediator of diverse knowledge flow, diverse knowledge consumer, and negative mediator of diverse knowledge flow. The case study related to synthetic biology indicates that this method is valid and could explore effectively, the roles of the research entities to further guide the creation of new inventions by converging prominent technologies beyond technology field boundaries in facilitating active technology flow and support technological competitive evaluation and policy decision-making.

Due to the expansion of data, search engines encounter different obstacles for retrieving better relevant content to user’s search queries. Consequently, various retrieval and ranking algorithms have been applied to satisfy the result’s relevancy according to user’s needs. Unfortunately, indexing and ranking processes face several challenges to achieve highly accurate results, since most of the existing indexes and ranking algorithms crawl documents and web pages based on limited number of criteria that satisfy user needs. So, this research studies and observes how search engines work and which factors contribute to higher rankings results. The research also proposes a Multi Criteria Indexing and Ranking Model (MCIR) based on weighted documents and pages which depend on one or more ranking factors, aiming at building a model that achieves high performance, better relevant pages, and the ability to index and rank both online/offline pages and documents. The MCIR model was applied on three different experiments to compare documents and pages results in terms of ranking scores, based on one or more criteria of user’s preferences. The results of applying MCIR model proved that final pages ranking results depending on multi-criteria are better than using only one criterion, and some criteria have great effect on ranking results than other criteria. It was also observed that the MCIR model achieved high performance on indexing and ranking dataset up to 100 gigabytes.

Massive physical devices are deployed in the industrial Internet of Things (IoT) to collect ambiance data while heavy storage and communication cost are imposed on these IoT devices. To overcome this constraint, cloud-assisted technologies are introduced to store and manage the collected data. In order to protect data quality and security, encryption is required before uploading data to remote clouds. Consequently, search function is added to cloud services to find the specific data. However, traditional data searching schemes are constructed in user-oriented systems, where the search function is mainly involved with the relationship between data and users rather than data and devices. As a result, traditional search schemes are not suitable to find special IoT devices. On the other hand, the status of these devices is described by many attributes, e.g., temperature, clean water storage, and machine speed in an early warning system for industrial sewage disposal equipment. Hence, multi-keyword conjunctive queries for partial attributes should be introduced so as to find the target device more accurately and more efficiently. To address these challenges, we propose a new universal device-oriented keyword searchable encryption scheme for cloud-assisted IoT in this paper. Furthermore, the functions of a single and conjunctive keyword search are maintained to handle the device search requirement of partial attributes. We conduct extensive experiments to evaluate the proposed scheme. Experimental results show that our scheme has excellent performance because of the lightweight index and query trapdoor.

Community search that finds query-dependent communities has been studied on various kinds of graphs. As one instance of community search, intimate-core group (community) search over a weighted graph is to find a connected k-core containing all query nodes with the smallest group weight. However, existing state-of-the-art methods start from the maximal k-core to refine an answer, which is practically inefficient for large networks. In this paper, we develop an efficient framework, called local exploration k-core search (LEKS), to find intimate-core groups in graphs. We propose a small-weighted spanning tree to connect query nodes, and then expand the tree to a connected k-core, which is finally refined as an intimate-core group. In addition, to support the intimate group search over large weighted graphs, we develop a weighted-core index (WC-index) and two new WC-index-based algorithms for expansion and refinement phases in LEKS. Specifically, we propose a WC-index-based expansion to efficiently find a candidate graph of intimate-core group, leveraging on a two-level expansion of k-breadth and 1-depth. We propose coarse-grained/fine-grained deletion strategies to achieve high-quality answers in a few iterations. Extensive experiments on real-life networks with ground-truth communities validate the effectiveness and efficiency of our proposed methods.

The purpose of this study is to show that direct speech in narratives introduced by “von wegen” (‘like’) and “nach dem Motto” (‘along the lines of’) can be analyzed as a powerful means to transform a stretch of talk into a massive “stance index” which transcends the boundaries between the narrator’s world and the narrated world in terms of narrative metalepsis. “Von wegen” and “nach dem Motto” are non-canonical reporting frames which are syntactically flexible and semantically facilitate a transformation of direct speech into a “category-animation”. For these reasons, they can be employed spontaneously in spoken talk-in-interaction and make it possible to shape a stretch of direct speech creatively in order to position oneself, other discourse participants and narrated characters as committed or non-committed to what is seen to be a relevant normative point of reference. The way direct speech introduced by “von wegen” and “nach dem Motto” can be used to construct positions in order to evaluate discourse participants and narrated characters can be grasped schematically by means of a slightly revised and extended version of Du Bois’ “stance triangle”.

This paper analyses the organization of ‘openings’ in Skype video-mediated conversation. It uncovers order in their apparent complexity by showing the relevance of a particular sequential adjacent pair organization, the appearing/noticing sequence, and its particular instantiation as an appearance-for-the-first-time greeting. The paper shows how this is a crucial resource in establishing a joint video interactional frame for the parties involved. This accounts for the occurrence of some specific phenomena in Skype openings, such as multiple greetings, and for the use of greetings which reflexively index their being occasioned by an appearance and related greeting, such as the French ‘coucou’, even when these do not occur at the start of Skype calls. When analysed this way, Skype openings, though complex, can be seen as an accomplished ‘dance of appearances and multiple greetings’.

This study applies the concepts of frames and performance roles (Bauman and Briggs 1990; Bauman 1993; Goffman 1974) to represented speech in personal narratives of speakers of Fulfulde, a Niger-Congo language of the (West) Atlantic group. Contextualization cues such as verbal suffixes indicating voice and aspect, person reference and references to states of knowledge index the frame of interaction between storyteller and audience, the frame of the narrated story, and an enacted frame that recontextualizes events within the story world. These cues also signal performance roles within the frame, such as the addressing self, the principal and the animator. The multiple frames and performance roles indexed by represented speech allow the speaker to represent past and present selves, and more importantly, to make an implicit comparison between the states of knowledge at various points in time in the performance of the narrative. In this way, the speaker distributes responsibility, blame and praise across multiple depictions of the self such that the one most accessible to the audience is portrayed as a superior representation of cultural ideals.

The grounds of authority for the Catalan language have shifted from authenticity to anonymity, as Catalan becomes redefined as a public language. The “model of language” of the Catalan press reflects this shift, with an emphasis on neutral, transparent Catalan. This article examines original and published letters to the editor in a Catalan-medium newspaper in Barcelona. I argue that standardization of language, page design and signatures in the letters to the editor erases the social indexicality that attaches the original letters to their socially positioned authors. This process of standardization in linguistic and other semiotic modes allows the published letters to index a unified Catalan national “public” rather than their distinct authors.

This paper investigates ways in which participants in everyday German narratives construct emotions as social phenomena; i.e. in particular, how they organize and communicate emotional involvement. I will argue that contextualizing emotions and affects permeates various levels of linguistic and interactional structures – even grammar: Participants in everyday German storytelling use specific syntactic patterns as resources for indexing affective stances and making past events interpretable and emotionally accessible to their co-participants. The analysis concentrates on particular syntactic resources (such as averbal constructions, infinite constructions, minimal syntactic phrases etc.) used to contextualize affect and emotion. Instead of treating these ‘dense constructions’ (e.g. averbal constructions “I:CH (.) mit meinen sachen rAuf, […] ICH (-) wieder rUnter,”; ‘me (.) with my stuff upstairs, […] me (-) down again,’) as elliptic structures and conceptualizing them as incomplete or reduced sentence patterns, this study explores the specific forms and functions of ‘dense constructions’ in interactive usage. I will argue that ‘dense constructions’ – even though they do not follow the rules of the grammar of Standard German – represent conventionalized patterns participants use to fulfil various communicative tasks in specific communicative genres. In producing such ‘fragmentary gestalts’, conversationalists index sudden, reflex-like actions, and thus, stage dramatic, emotionally loaded events for their co-participants to “re-experience” (Goffman 1974/1986: 506).

This paper draws together discussions around public and private, represented talk, and conviviality by showing how an interviewee uses linguistic features to frame instances of talk as either “represented private talk” or “represented public talk”. My empirical focus is an interview that was recorded as part of fieldwork on leadership practices in the Indonesian bureaucracy. In this interview with a department head it seems that he adds authenticity to accounts of his leadership practices by performing them through represented talk. His use of Javanese in instances of represented talk also helps index intimate social relations between himself and his staff, while in some instances the combination of reference to place and participants also helps to nest ideas of private within represented public talk.

An echo answer is an answer that repeats elements of the question. This response form occurs after yes/noquestions and “statements about B-events”. The current study is based on data from native/non-native institutional interaction, and echo answers are shown to play an important role in certain types of repair that are characteristic of such interaction. Echo answers have two main usages. The first is to appropriate a candidate formulation and integrate it into one’s own turn in progress. This often happens when native speakers attempt to assist non-native interlocutors in expressing themselves. The other is to claim a strengthened commitment to the answer. This is especially salient in cases where a minimal agreement might project a potential dispreferred response. Echo answers may occur alone or with an initial or final response word, and these different response formats are shown to index the relative epistemic authority of the interlocutors.

Social Internet of Things (SIoT) incorporates social relationship into Internet of Things, and compositive relationship between persons, devices and persons to devices is utilized for providing better services. This paper proposes a novel type of search, namely top-k social spatial keyword search (SSKS) in SIoT networks to discover relevant users or data objects according to social, spatial and textual preferences. Existing works mainly focus on two of these preferences at the same time, and efficiently processing top-k SSKS remains challenging. To this end, we propose two algorithms to evaluate top-k SSKS in SIoT networks. The first algorithm is a forward search based algorithm, which spreads the search from the vertex of the querying user. An effective pruning strategy is established by recognizing an early termination condition according to the threefold preference. The forward search based algorithm is efficient when textual objects are dense. The second algorithm is based on index searching. We present an index namely 2HL-GIL to support spatial and textual pruning while providing fast computation of social distances in the SIoT. Then an index-based search algorithm is proposed for top-k SSKS, and it is efficient especially when textual objects are sparse. Our proposed algorithms are evaluated over two real-life social networks attached with synthetic locations and textual data. Evaluation results illustrate the effectiveness and efficiency of our proposed forward search based algorithm and index-based search algorithm.

Objectives Consent forms that are difficult to understand may jeopardize informed consent. The aim of this study was to determine whether consent documents for cardiology-related procedures could be easily read and understood by patients with low health literacy. Methods All 37 cardiology-related consent forms with patient information material were retrieved from a publicly available suite of documents from one state in Australia. Two raters independently assessed documents and resolved discrepancies through discussion. Understandability was assessed using the Patient Education Materials Assessment Tool for Printed materials (PEMAT-P). Readability was assessed using the Gunning Fog Index, SMOG and Flesch Reading Ease formulas. Images were assessed using the 5C Image checklist. Results were analyzed descriptively. Results Only 1 of 37 forms met the general PEMAT-P threshold (70%) for being ‘understandable’. The average readability score was high, requiring a grade 10–12 level of education to understand. Most images lacked useful captions, had low visual clarity, and were not purpose-designed for the material. Conclusions The current format for cardiology consent forms does not meet recommended standards for understandability and readability. Practice implications Development of consent forms would benefit from taking health literacy principles into account with patient input, and purpose-designed images should be included in all forms to reinforce text.

Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can make database more intelligent (AI4DB). For example, traditional empirical database optimization techniques (e.g., cost estimation, join order selection, knob tuning, index and view selection) cannot meet the high-performance requirement for large-scale database instances, various applications and diversified users, especially on the cloud. Fortunately, learning-based techniques can alleviate this problem. On the other hand, database techniques can optimize AI models (DB4AI). For example, AI is hard to deploy in real applications, because it requires developers to write complex codes and train complicated models. Database techniques can be used to reduce the complexity of using AI models, accelerate AI algorithms and provide AI capability inside databases. Thus both DB4AI and AI4DB have been extensively studied recently. In this paper, we review existing studies on AI4DB and DB4AI. For AI4DB, we review the techniques on learning-based configuration tuning, optimizer, index/view advisor, and security. For DB4AI, we review AI-oriented declarative language, AI-oriented data governance, training acceleration, and inference acceleration. Finally, we provide research challenges and future directions.

BACKGROUND A new bibliometric index called the disruption score was recently proposed to identify innovative and paradigm-changing publications. OBJECTIVE The goal was to apply the disruption score to the colorectal surgery literature to provide the community with a repository of important research papers. DESIGN A bibliometric analysis. SETTINGS The 100 most disruptive and developmental publications in Diseases of the Colon and Rectum, Colorectal Disease, International Journal of Colorectal Disease, and Techniques in Coloproctology were identified from a validated dataset of disruption scores and linked with the iCite NIH tool to obtain citation counts. MAIN OUTCOME MEASURES Disruption score and citation count. RESULTS We identified 12,127 articles published in Diseases of the Colon and Rectum (n=8,109), International Journal of Colorectal Disease (n=1,912), Colorectal Disease (n=1,751), and Techniques in Coloproctology (n=355) between 1954-2014. Diseases of the Colon and Rectum had the most papers in the top 100 most disruptive and developmental lists. The disruptive papers were in the top 1% of the disruption score distribution in PubMed and were cited between 1 and 671 times. Being highly cited was weakly correlated with high disruption scores (r=0.09). Developmental papers had disruption scores that were more strongly correlated with citation count (r=0.18). LIMITATIONS Subject to limitations of bibliometric indices, which change over time. DISCUSSION The disruption score identified insightful and paradigm-changing studies in colorectal surgery. Interestingly, they include a wide range of topics and consistently identified editorials and case reports/case series as important research. This bibliometric analysis provides colorectal surgeons with a unique archive of research that can often be overlooked, but that may have scholarly significance. See Video Abstract at http://links.lww.com/DCR/B639 .

Content-Based Image Retrieval (CBIR) systems have recently emerged as one of the most promising and best image retrieval paradigms. To pacify the semantic gap associated with CBIR systems, the Bag of Visual Words (BoVW) techniques are now increasingly used. However, existing BoVW techniques fail to capture the location information of visual words effectively. This paper proposes an unsupervised Content-Based Medical Image Retrieval (CBMIR) framework based on the spatial matching of the visual words. The proposed method efficiently computes the spatial similarity of visual words using a novel similarity measure called the Skip Similarity Index. Experiments on three large medical datasets reveal promising results. The location-based correlation of visual words assists in more accurate and efficient retrieval of anatomically diverse and multimodal medical images than the state-of-the-art CBMIR systems.

Electronic patient record (EPR) gains popularity in the health care system with easy availability and usually employs searchable encryption to guarantee both record confidentiality and record retrieval. However, traditional searchable encryption schemes cost a linear complexity of database and even reveals the query index. Both problems hinder EPR applications thereby balancing privacy and search efficiency becomes challenging. In this paper, we design a cryptographically searchable EPR system named FastPRS which supports strong privacy and high performance. FastPRS is built on top of online/offline puncturable search (OOPS), a newly defined primitive which splits the search process into the offline phase and the online phase and embeds an index in puncturable pseudorandom sets. Leveraging a combination of linearly homomorphic encryption and oblivious transfer, the query index is punctured. OOPS, therefore, hides the query index obliviously and reduces the search complexity to a sublinear size. We also implement a FastPRS prototype system that supports more than 60,000 keywords and evaluation results show that FastPRS optimizes the search efficiency to 417 search operations per millisecond.

Huge amounts of spatio-textual objects are being generated at an unprecedented scale, leading to a variety of applications such as location-based recommendation and sponsored search. Many of these applications need to support moving top-k spatio-textual subscriptions. Unfortunately, existing methods that monitor the results of spatio-textual subscriptions support only static top-k subscriptions or moving boolean subscriptions. In this paper, we propose a novel system, called Lamps (Location-Aware Moving Top-k Pub/Sub), which continuously monitors the top-k most relevant spatio-textual objects for a large number of moving top-k spatio-textual subscriptions simultaneously. As with existing works on continuous moving top-k subscription processing, Lamps employs the concept of a safe region to monitor top-k results. However, unlike with existing works that assume static objects, top-k result updates may be triggered by newly generated objects. To continuously monitor the top-k results for massive moving subscriptions efficiently, we propose SQ-Tree, a novel index based on safe regions, to filter subscriptions whose top-k results do not change. Moreover, to reduce the expensive cost of safe region re-evaluation, we develop a novel approximation technique for safe region construction. Our experimental results on real datasets show that Lamps achieves higher performance than baseline approaches.

Aiming at disclosing a general research landscape of structural engineering in the twenty-first century, this study applies the latent Dirichlet allocation (LDA), a topic modeling approach, to analyze 51,346 article abstracts from 23 prestigious journals in structural engineering with a publication period from 2000 to 2020. The LDA analyzes the literature inventory by extracting 50 distinguishable wordclouds, each centered around one distinct research theme and assigned a unique topic name. Subsequently, various measures have been proposed to integrate the posterior distributions of these research topics with article information such as publication year, journal name, and correspondence address. The increase index identifies five cold and hot topics, which reflect the shift of research interests in the community. Emerging research topics such as seismic risk assessment and composite material have received much more attention in recent years. Moreover, advanced metrics have been proposed to analyze the research similarity and evolution across different journals and countries/regions. As discussed in the paper, analysis findings would enable community stakeholders (e.g., students, engineers, researchers, conference organizers, journal editors, funding agencies) to explore the state of the research and develop viable strategies to further foster the healthy growth of the community. Such strategies can be (1) researchers submitting a paper to the most appropriate journal; (2) journal editors adjusting the journal focus to enhance its impact; and (3) funding agencies prioritizing research supports that best fit regional needs and circumstances, among others.

In the era of cloud computing, to achieve convenient location-based service (LBS), consumers such as users, companies, and organizations prefer subcontracting massive geographical data to public clouds after encryption for privacy and security. However, numerous harmful cyber-attacks happen on those public clouds in an unpredicted and hourly manner. To alleviate those concerns, various secure query schemes on the encrypted data have been proposed in the literature. As a fundamental query of LBSs, forward-secure range query has not been well investigated. To address this issue, we propose a lightweight and forward-secure range query (LS-RQ) on geographically encrypted data, which soundly balances between security and efficiency. Promisingly, we design an index mechanism to manage geographical data on the public clouds, while not compromising the privacy of data. Moreover, our LS-RQ schemes provide a convenient approach to range query on geographically encrypted data on-the-fly. We also rigorously prove that LS-RQ is forward-secure. Finally, extensive experimental studies are performed on both real and synthetic datasets. By observation, our LS-RQ schemes are highly efficient in realistic environments. Particularly, on encrypted datasets with about 1, 000, 000 geographical data, our solution to secure range query takes strictly less than a second.

Smartwatch (SW) is a wearable gadget used in everyday life. It is equivalent to a customary wristwatch and offers features similar to a smartphone. These features include access to the internet, making a call, weather updates, text or video messages, GPS navigation, health, physical fitness information, etc. The market for wearable gadgets and SWs is increasing day by day. There are many benefits and drawbacks of smartwatches in medical environments. This article aims to review the existing literature on smartwatch applications in the biomedical sector. As a result, this paper compiles all the information regarding SW technology in the biomedical sector and related journal articles, conference proceedings, web materials, market survey reports, and history in one place. The review shows that the demand rate of SWs in India is less as compared to other countries. It is increasing with the years, but the overall rate of demand is not as expected. It varies with the user’s choice. The vital author keyword and index keywords are presented. The abstract and title words are also analyzed with Vosviewer 1.6.16 software. The attributes/criteria associated with SWs are also discussed, which helps in purchasing them. The paper also discusses the flaws and problems that need to be resolved in the present situation and several potential alternatives for prospective research projects.

The theatre magazine Artist has repeatedly become an object of scientific research. However, despite the wealth of works with a focus on structure of the magazine, the bibliographic section of Artist remains insufficiently studied. The bibliographic information of the journal has not yet become an object of subject-specific research. The empirical basis of the study is a complete set of publications of the theater magazine Artist for the entire period of its existence. Primary attention is paid to the bibliographic section of the journal and the appendix. Research methods are theoretical and historical analysis, generalization and systematization of the results obtained. In the proposed article, the author describes and comprehends the main forms of latent bibliographic information in the theatrical magazine Artist, first of all, the independent section Bibliography. The study defines main thematic areas of the section, its structure and main genres. The author also analyzes the types of bibliographic advertising in the journal: alphabetical directories of plays allowed to be performed, index of plays suitable for amateur shows, announcements on subscription from magazine editors, advertising of new books, ads for subscriptions to other print media. The author comes to the conclusion that along with educational intentions, the magazine staff solved specific selling tasks (sale of the magazine and books distributed through the publishers office). The latent bibliographic information of Artist can be useful for specialists interested in history of literature, journalism and theatre.

Background Empowerment among older adults is a key concept for improving their health. In contrast, empowerment evolves according to cultural and historical contexts and needs to be consistently tested and constructed. The purpose of this study was to clarify the components of older adults’ empowerment in contemporary Japan and to reconstruct the definition of empowerment. Methods A conceptual analysis was performed using Rodgers’ evolutionary method. The data sources were PubMed, Cumulative Index to Nursing and Allied Health Literature, Web of Science, Cochrane Library, and Igaku Chuo Zasshi. The search keywords were “empowerment,” “older adults,” and “Japan/Japanese.” Of the 8811 articles published between 2000 and 2019 that focused on older adults’ empowerment, we selected 60 articles that met our objectives. Results Seven antecedents, six attributes, and seven consequences were identified. Older adults’ empowerment in contemporary Japan was defined as “the series of processes in which disclosing oneself, not only verbally but also nonverbally (e.g., through work, roles, and collaborative activities), in connection with others, objectively perceiving one’s existence and challenges, taking proactive actions based on decision-making, and utilizing one’s strengths in new work and community life.” Conclusions This concept is useful in practice, education, and research on community development and providing support for older adults based on self-help and mutual aid, not only in Japan but also for the global aging society.

Problem and goal. The practical (pedagogical) training sites based on Moscow schools in the context of effective development of the resources of the Moscow Electronic School by future computer science teachers are analyzed. The goal is to identify the correlation of the digital footprint obtained as a result of the development of the school network activity index based on data on the actions of teachers and students in e-learning environments and of educational organizations identification corresponding to this index, as well as the methodological activity of schools in Moscow - the bases of practical (pedagogical) training of future computer science teachers. Methodology. The analysis of regulatory documents and the database of Moscow schools, where the Moscow City University students of the Computer Science direction are engaged in practical (pedagogical) training, reflection on the content of the knowledge obtained, search for criteria for selecting basic schools for conducting practical (pedagogical) training of future computer science teachers, local pedagogical experiment were used. Results. It was found out that the activity of schools in the development and use of educational resources of the Moscow Electronic School is not a prerequisite for cooperation with these schools. At the same time, the knowledge of information technologies, including the technology of working with the resources of the Moscow Electronic School, by future subject teachers, is an integral part of the professional competence of a modern teacher, and especially a computer science teacher. Conclusion. The basic criteria for selecting sites for industrial practices of future computer science teachers, in particular students of the Moscow City University, are proposed. The formulated criteria for selecting basic schools for conducting practical (pedagogical) training of university students will allow them to successfully solve the tasks set for this type of educational activity, achieve their goals and form professional and pedagogical competencies.

Index coding and coded caching are two active research topics in information theory with strong ties to each other. Motivated by the multi-access coded caching problem, we study a new class of structured index coding problems (ICPs) which are formed by the union of several symmetric ICPs. We derive upper and lower bounds on the optimal server transmission rate for this class of ICPs and demonstrate that they differ by at most a factor of two. Finally, we apply these results to the multi-access coded caching problem to derive better bounds than the state of the art., Comment: 44 pages, single column, ITW and JSAIT

The author of this intellectually stimulating book, Christopher J. Shepherd, an anthropologist, has an experience of fieldwork in East Timor. The book addresses the period from the second half of the 19th century to 1975. In a ground-breaking “anthology” of ethnographic writing and practice, Shepherd provides a discursive analysis of fieldwork’s methodology and background on the Eastern region of the island. Ethnographic locations of anthropologists are considered in the line of Clifford and ...

Reachability is a fundamental problem in graph analysis. In applications such as social networks and collaboration networks, edges are always associated with timestamps. Most existing works on reachability queries in temporal graphs assume that two vertices are related if they are connected by a path with non-decreasing timestamps (time-respecting) of edges. This assumption fails to capture the relationship between entities involved in the same group or activity with no time-respecting path connecting them. In this paper, we define a new reachability model, called span-reachability, designed to relax the time order dependency and identify the relationship between entities in a given time period. We adopt the idea of two-hop cover and propose an index-based method to answer span-reachability queries. Several optimizations are also given to improve the efficiency of index construction and query processing. We conduct extensive experiments on eighteen real-world datasets to show the efficiency of our proposed solution.

Esh is an emblematic word and sound in global beatboxing culture. It may have developed from the vocal mimicry of a sound of a snare drum or it may have derived from multicultural youth slang in France. What is clear is that esh is now widely recognized and used as a lexicalized sound to humorously index cultural identity alignments, for example taking a stance of affirmative evaluation, greeting and identifying other beatboxers. We show in this article how beatboxers perform, narrativize and mediatize the interactive functions and cultural indexicalities of esh. This enregisterment, we argue, is schizophonic, i.e. esh is indexically anchored in a mimetic shapeshifting between humans and machines.

A new class of graphs G(w), called Parikh word representable graphs (PWRG), corresponding to words $w$ that are finite sequence of symbols, was considered in the recent past. Several properties of these graphs have been established. In this paper, we consider these graphs corresponding to binary core words of the form $aub$ over a binary alphabet {a,b}. We derive formulas for computing the Wiener index of the PWRG of a binary core word. Sharp bounds are established on the value of this index in terms of different parameters related to binary words over {a,b} and the corresponding PWRGs. Certain other Wiener-type indices that are variants of Wiener index are also considered. Formulas for computing these indices in the case of PWRG of a binary core word are obtained.

The currently prevailing international ranking systems for institutions are limited in their assessment as they only provide assessments either at an overall level or at very broad subject levels such as Science, Engineering, Medicine, etc. While these rankings have their own usage, they cannot be used to identify best institutions in a specific subject (say Computer Science) by taking into account their performance in different thematic areas of research of the given subject (say Artificial Intelligence or Machine Learning or Computer Vision etc. for the subject Computer Science). This paper tries to bridge this gap by proposing a framework that uses the NLP and Network approach for identifying the core competency of institutions and their thematic research strengths. The core competency can be viewed as a measure of breadth of research capability of an institution in a given subject, whereas thematic research strength can be viewed as depth of research of the institution in a specific theme of a subject. The working of the framework is demonstrated in the area of Computer Science for 195 Indian institutions. The framework can be useful for institutions and the scientometrics research community as a system providing a detailed assessment of the core competency and the research strengths of institutions in different thematic areas. The framework and outcomes can also be useful for funding agencies in devising programs for ‘performance-based funding’ in ‘thrust areas’ or ‘national priority areas’.

According to the portal Math-Net.Ru a graph of journal citation is constructed. To increase the reliability of the model, the citation time interval was chosen from 2010 to 2021, when the distribution of citation articles stabilized at the level of 3500-4500 citations per year. The structure of link aging is studied and it is shown that their half-life is equal to 8 years. Therefore, the publication date of the cited articles was limited to 2002. For the constructed citation graph, the main properties, such as a small diameter and a high density, are obtained, indicating a high level of scientific communication in the Math-Net.Ru. The absence of the “Matthew effect” as a pronounced advantage in quoting established journals in relation to less well-known ones is shown. Adequacy of the journal citation graph Math-Net.Ru as a model of scientific communication confirmed by comparing the ranking of journals in the citation graph with their SCIENCE INDEX rating in eLIBRARY.RU. A direct moderate relationship between the two rankings is shown. A number of meaningful conclusions are drawn from the analysis of the citation graph.

One's work can be done efficiently only if their mood is good. Emotions is the index of mood. Here model capture one's image as an input, predict their mood and play a video of opposite genre as an output, in order to change their mood, which is the main goal of this project. Hence taking them through an emotional roller coaster. The solution makes use of CNN (convolutional neutral networks) for detecting one's mood. It uses OpenCV (open-source computer vision library) in-order to get user's image using their respective web camera. It is done by importing modules like web-browser and requests in-order to get access to YouTube to play videos accordingly. The average accuracy rate of the system has increased to 98.53 percent. Eight primary emotion classes have been effectively classified by the method. As a result, the proposed strategy has been shown to be effective in recognising emotions.

A complete pipeline is presented for accurate and efficient partial 3D object retrieval based on Quick Intersection Count Change Image (QUICCI) binary local descriptors and a novel indexing tree. It is shown how a modification to the QUICCI query descriptor makes it ideal for partial retrieval. An indexing structure called Dissimilarity Tree is proposed which can significantly accelerate searching the large space of local descriptors; this is applicable to QUICCI and other binary descriptors. The index exploits the distribution of bits within descriptors for efficient retrieval. The retrieval pipeline is tested on the artificial part of SHREC'16 dataset with near-ideal retrieval results., Comment: 19 pages, 17 figures, to be published in Computers & Graphics

This is the world’s first tutorial article on Python Packaging for beginners and practitioners for translational medicine or medicine in general. This tutorial will allow researchers to demonstrate and showcase their tools on PyPI packages around the world. Nowadays, for translational medicine, researchers need to deal with big data. This paper describes how to build an executable Python Package Index (PyPI) code and package. PyPI is a repository of software for the Python programming language with 5,019,737 files and 544,359 users (programmers) as of 19 October 2021. First, programmers must understand how to scrape a dataset over the Internet; second, they must read the dataset file in csv format; third, build a program to compute the target values; fourth, convert the Python program to the PyPI package.; and fifth, upload the PyPI package. This paper depicts a covidlag executable package as an example for calculating the accurate case fatality rate (CFR) and the lag time from infection to death. You can install the covidlag by pip terminal command and test it. This paper also introduces deathdaily and scorecovid packages on PyPI Stats, which can inform how many users have downloaded the specified PyPI package. The usefulness and applicability of a developed tool can be verified by PyPI Stats with the number of downloaded users.

In screen studies and photography studies, the name of the acclaimed film theorist and critic André Bazin is frequently invoked by scholars seeking to defend the import of analogue media on ontological grounds by citing photography's privileged connection to the real. This article seeks to unsettle Bazin's reputation as the patron saint of analogue recording by exploring the ontological implications of the concept of sense in Bazin's writings on neorealism. Placing Bazin's writings into dialogue with a selection of critiques that find the digital image to be lacking in historicity, negativity, and presence, and flag its potentially authoritarian impulses, this essay seeks to reframe Bazin's ontological project as a question of cinema's sense (rather than its essence) to mobilize a different set of conclusions that may in fact prove to restore faith in the digital image and its rapport with the real. By maintaining that what is often treated as a purely technological problem also harbors aesthetics implications, this article confronts the manifest skepticism that has pervaded the discourse around the digital since the 1990s, seeking an alternative outlook in Jean-Luc Nancy's work on sense, an ontological concept that evidences the political potentials (or potential politics) of Bazin's predilection for images, which are said to ameliorate our love for reality by transmitting the excessive sense of the world in its ambiguity, creativity, and unpredictability.

EuroVoc is a thesaurus maintained by the European Union Publication Office, used to describe and index legislative documents. The EuroVoc concepts are organized following a hierarchical structure, with 21 domains, 127 micro-thesauri terms, and more than 6,700 detailed descriptors. The large number of concepts in the EuroVoc thesaurus makes the manual classification of legal documents highly costly. In order to facilitate this classification work, we present two main contributions. The first one is the development of a hierarchical deep learning model to address the classification of legal documents according to the EuroVoc thesaurus. Instead of training a classifier for each hierarchy level, our model allows the simultaneous prediction of the three levels of the EuroVoc thesaurus. Our second contribution concerns the proposal of a new legal corpus for evaluating the classification of documents written in Portuguese. This corpus, named EUR-Lex PT, contains more than 220k documents, labeled under the three EuroVoc hierarchical levels. Comparative experiments with other state-of-the-art models indicate that our approach has competitive results, at the same time offering the ability to interpret predictions through attention weights.

In the process of online course resource recommendation, the output of recommendation results is often unstable. Therefore, a physical education online course resource recommendation method based on collaborative filtering technology is proposed. Firstly, the learning preference of e-learners is calculated, the frequency index of the word frequency-inverse document is defined, the correlation between courses is reflected, and the specific needs of students for PE online course resource recommendation are understood. Then, the collaborative filtering recommendation algorithm is used to generate the similarity matrix and correlation matrix, update the edge characteristics of sports online curriculum resources, collect and refine the hidden index of sports online curriculum resources, optimize the prediction rules of the neighborhood of the most similar teaching unit, and complete the recommendation of sports online curriculum resources. Experimental results show that, for 1000 keywords, the method has the highest single average matching degree, the recommendation process is stable, and the F1 value is more than 0.9, and the practical application is ensured.

As an important biomedical database, PubMed provides users with free access to abstracts of its documents. However, citations between these documents need to be collected from external data sources. Although previous studies have investigated the coverage of various data sources, the quality of citations is underexplored. In response, this study compares the coverage and citation quality of five freely available data sources on 30 million PubMed documents, including OpenCitations Index of CrossRef open DOI-to-DOI citations (COCI), Dimensions, Microsoft Academic Graph (MAG), National Institutes of Health Open Citation Collection (NIH-OCC), and Semantic Scholar Open Research Corpus (S2ORC). Three gold standards and five metrics are introduced to evaluate the correctness and completeness of citations. Our results indicate that Dimensions is the most comprehensive data source that provides references for 62.4% of PubMed documents, outperforming the official NIH-OCC dataset (56.7%). Over 90% of citation links in other data sources can also be found in Dimensions. The coverage of MAG, COCI, and S2ORC is 59.6%, 34.7%, and 23.5%, respectively. Regarding the citation quality, Dimensions and NIH-OCC achieve the best overall results. Almost all data sources have a precision higher than 90%, but their recall is much lower. All databases have better performances on recent publications than earlier ones. Meanwhile, the gaps between different data sources have diminished for the documents published in recent years. This study provides evidence for researchers to choose suitable PubMed citation sources, which is also helpful for evaluating the citation quality of free bibliographic databases., Scientometrics (2021)

Verifying imperative programs is hard. A key difficulty is that the specification of what an imperative program does is often intertwined with details about pointers and imperative state. Although there are a number of powerful separation logics that allow the details of imperative state to be captured and managed, these details are complicated and reasoning about them requires significant time and expertise. In this paper, we take a different approach: a memory-safe type system that, as part of type-checking, extracts functional specifications from imperative programs. This disentangles imperative state, which is handled by the type system, from functional specifications, which can be verified without reference to pointers. A key difficulty is that sometimes memory safety depends crucially on the functional specification of a program; e.g., an array index is only memory-safe if the index is in bounds. To handle this case, our specification extraction inserts dynamic checks into the specification. Verification then requires the additional proof that none of these checks fail. However, these checks are in a purely functional language, and so this proof also requires no reasoning about pointers.

Next-generation enterprise management systems are beginning to be developed based on the Systems of Engagement (SOE) model. We visualize an SOE as a set of entities. Each entity is modeled by a single parent document with dynamic embedded links (i.e., child documents) that contain multi-modal information about the entity from various networks. Since entities in an SOE are generally queried using keywords, our goal is to efficiently retrieve the top-k entities related to a given keyword-based query by considering the relevance scores of both their parent and child documents. Furthermore, we extend the afore-mentioned problem to incorporate the case where the entities are geo-tagged. The main contributions of this work are three-fold. First, it proposes an efficient bitmap-based approach for quickly identifying the candidate set of entities, whose parent documents contain all queried keywords. A variant of this approach is also proposed to reduce memory consumption by exploiting skews in keyword popularity. Second, it proposes the two-tier HI-tree index, which uses both hashing and inverted indexes, for efficient document relevance score lookups. Third, it proposes an R-tree-based approach to extend the afore-mentioned approaches for the case where the entities are geo-tagged. Fourth, it performs comprehensive experiments with both real and synthetic datasets to demonstrate that our proposed schemes are indeed effective in providing good top-k result recall performance within acceptable query response times.

The use of information technology is an integral part of the learning process in the University. The research aimed to find out empirical evidence of the impact of electronic information resources on improving the academic performance of students in the Management Study Program. The research model used mediation regression with SEM and the PLS statistical software. Purposive sampling with 210 respondent. Electronic information resources were measured by the availability of software application infrastructure, online journals, online databases, institutional repositories, e-books, e-journals, and websites. Electronic information resources were measured by using skills electronic information resources in the learning process, making final assignments, publications. Academic performance was measured from the teaching and learning process, publications of students, improvement of achievement index, contribution to society. The results showed that the availability of software application infrastructure, online journals, online databases, institutional repositories, e-books, e-journals, and websites had an effect on academic performance. Habits or use fullness of using electronic information resources mediated the effect of electronic information resources on academic performance.

The COVID-19 pandemic requires lecturers to change learning strategies through online learning. The use of technology which has grown exponentially in the world of education requires students to be proficient in using technology in finding information as a source of knowledge. To be able to prepare competitively students in this 4.0 education era, an instrument is needed to find out to what extent students' digital literacy abilities are. This research is development research (R&D) which aims to develop a Digital Literacy Assessment Scale (DLAS) instrument to measure students' digital literacy skills. The procedure of this research includes determining the construct and specifications of the instrument, writing the items, and analyzing the items. Based on the results, the DLAS instrument has a total of 52 items consisting of 3 aspects including access to information (access), student involvement in academic activities (behavioral engagement), and socio-emotional (socio-emotional). The results of content validity carried out by 5 expert judgments showed that the DLAS instrument was proven to be content valid with the acquisition of Aiken's V index of 0.87.

Objectives: The aim of the present study is to evaluate the accuracy and reliability of the information provided in the videos about the clear aligner on the Youtube video platform, an internet information source. Materials and Methods: A video search was performed on the Youtube video platform using three keywords determined with the Google Trends application. After the videos were ranked based on their view counts, a total of 75 videos were analyzed, 47 being the first for each term. After applying the exclusion criteria (repetitive content, no audio content or title information, irrelevant to the topic, only promotional content, duration over 15 min, and addressing other orthodontic treatments), the remaining 47 videos were evaluated. Regarding the videos, the following parameters were recorded: View count, number of likes, number of dislikes, number of comments, video duration, and days since the uploaded date. A scoring system consisting of seven parameters was used to classify the video content quality as low and high. The video information and quality index were utilized to evaluate the quality of the videos universally. Statistical analyses were performed with Stata/IC computer program using Shapiro–Wilks, Kruskall–Wallis, Mann–Whitney U, and linear regression (Backward method) tests. Statistical significance value was set at P < 0.05. Results: Evaluation of the videos based on their upload source revealed that 27 videos were downloaded from individuals, ten videos from doctors and ten videos from commercial sources, and the number of subscribers to these sources varied significantly (P < 0.05). Evaluation of the videos based on the information provided, revealed that 32 videos had poor quality, ten videos had moderate quality and five videos had good quality information content, and the video durations varied significantly (P < 0.05). It was seen that of the 75 videos viewed, only 10 (13.3%) provided information of moderate-good quality. The number of likes was found to be the parameter that significantly affects the view count (P < 0.05). Conclusion: YouTube videos prove insufficient as a source of information on orthodontic treatment with clear aligner. Health-care professionals should be aware of online platforms to ensure that patients can access accurate information.

Author‐level metrics are a widely used measure of scientific success. The h‐index and its variants measure publication output (number of publications) and research impact (number of citations). They are often used to influence decisions, such as allocating funding or jobs. Here, we argue that the emphasis on publication output and impact hinders scientific progress in the fields of ecology and evolution because it disincentivizes two fundamental practices: generating impactful (and therefore often long‐term) datasets and sharing data. We describe a new author‐level metric, the data‐index, which values both dataset output (number of datasets) and impact (number of data‐index citations), so promotes generating and sharing data as a result. We discuss how it could be implemented and provide user guidelines. The data‐index is designed to complement other metrics of scientific success, as scientific contributions are diverse and our value system should reflect that both for the benefit of scientific progress and to create a value system that is more equitable, diverse, and inclusive. Future work should focus on promoting other scientific contributions, such as communicating science, informing policy, mentoring other scientists, and providing open‐access code and tools., Our current value system in academia centers around publications. This hinders scientific progress as it disincentivizes fundamental practices, such as generating and sharing data. Here, we describe a new author‐level metric (the data‐index) which values these practices and promotes them as a result. The data‐index is designed to complement other indices of scientific success, and create a broader perspective of scientific impact.

HDFS faces several issues when it comes to handling a large number of small files. These issues are well addressed by archive systems, which combine small files into larger ones. They use index files to hold relevant information for retrieving a small file content from the big archive file. However, existing archive-based solutions require significant overheads when retrieving a file content since additional processing and I/Os are needed to acquire the retrieval information before accessing the actual file content, therefore, deteriorating the access efficiency. This paper presents a new archive file named Hadoop Perfect File (HPF). HPF minimizes access overheads by directly accessing metadata from the part of the index file containing the information. It consequently reduces the additional processing and I/Os needed and improves the access efficiency from archive files. Our index system uses two hash functions. Metadata records are distributed across index files using a dynamic hash function. We further build an order-preserving perfect hash function that memorizes the position of a small file's metadata record within the index file.

The functional interpretation of two salient language-sensitive ERP components - the N400 and the P600 - remains a matter of debate. Prominent alternative accounts link the N400 to processes related to lexical retrieval, semantic integration, or both, while the P600 has been associated with syntactic reanalysis or, alternatively, to semantic integration. The often overlapping predictions of these competing accounts in extant experimental designs, however, has meant that previous findings have failed to clearly decide among them. Here, we present an experiment that directly tests the competing hypotheses using a design that clearly teases apart the retrieval versus integration view of the N400, while also dissociating a syntactic reanalysis/reprocessing account of the P600 from semantic integration. Our findings provide support for an integrated functional interpretation according to which the N400 reflects context-sensitive lexical retrieval - but not integration - processes. While the observed P600 effects were not predicted by any account, we argue that they can be reconciled with the integration view, if spatio-temporal overlap of ERP components is taken into consideration.

Aim: The aim of this study was to assess YouTube videos about COVID-19 in relation to orthodontics. Methodology: A YouTube search using the keyword “coronavirus orthodontics” was conducted on January 11, 2021. The top 50 videos were evaluated. The exclusion criteria were as follows: videos in other languages, duplicates, irrelevant videos, and duration longer than 15 minutes. The remaining 22 videos were scored by one examiner. Each of these videos was classified into one of three categories: useful, misleading, or news update. The modified DISCERN reliability index, number of views, number of comments, duration (in minutes), number of likes and dislikes, interaction index, viewing rate, and source of each video were also recorded. Results: Useful videos accounted for 77% of those examined, misleading videos accounted for 14%, and news updates accounted for 9%. Most of the videos were uploaded by orthodontists (95%) and most of these were classified as useful (81%). Useful videos had a significantly higher DISCERN score than misleading videos (p

Aim: Oral cancer is one of the health problems that results in high mortality in the community. It is known that, when diagnosed in the later stages (3 or 4), the disease is difficult to treat. Patient education on heredity and early diagnoses are critical for the successful treatment of oral cancer. This study aimed to evaluate Turkish texts about oral cancers found online in terms of their readability and content. Methodology: The first 100 websites returned from a Google search using the keywords "Ağız kanseri" (“oral cancer,” in Turkish) were examined. The patient information texts obtained were evaluated according to the Ateşman Readability Index. Their contents were also evaluated in terms of whether or not they provided sufficient information about the disease. Results: It was understood that the texts examined in the study were of medium difficulty according to the Ateşman Readability Index (mean 61.73± 11.81). The content of the information on the websites examined in the study was deemed sufficient and useful. Most of the websites examined were those of private clinics and hospitals. Conclusion: The results of the study indicated that the patient information texts found on Turkish websites were of medium reading difficulty. Although they are sufficient in terms of content, if they are not understood by the patients, their intended effects on readers will not be seen. How to cite this article: Kaya DI. Readability and content assessment of patient information texts on oral cancers found on Turkish websites. Int Dent Res 2021;11(Suppl.1):91-5. https://doi.org/10.5577/intdentres.2021.vol11.suppl1.15 Linguistic Revision: The English in this manuscript has been checked by at least two professional editors, both native speakers of English.