Reviewerly/exHarmony huggingface dataset:
A Short-Term Biometric Based System for Accurate Personalized Tracking

Surveillance systems have long been in the focus of the research community. Although the accurate detection of the human presence in the scene is now possible even under extreme environmental conditions via the advanced modern camera sensors, efficient personalized tracking is still an open issue and a significant challenge for researchers addressing. Moreover, personalized tracking will not only enhance the tracking robustness but it can also find useful application in several commercial surveillance use-cases, ranging from security to occupancy statistics (i.e. per building, per space and per human). In this respect, this paper introduces a novel the biometric approach for enhanced privacy preserving human tracking based on a novel soft-biometric feature of humans. The moving blobs in the recorded scene can be easily detected in the colour images, while the human silhouettes are detected from the corresponding depth ones. The state-of-the-art 3D Weighted Walkthroughs (3DWW) transformation is applied on the extracted human 3D point cloud, forming thus, a short-term soft biometric signature. The re-authentication of the humans is performed via the comparison of their last valid signature with current one. A thorough analysis on the adjustment of the system’s optimal operational settings has been carried out and the experimental results illustrate the promising robustness, accuracy and efficiency on human tracking performance.
Robust Regression Random Forests by Small and Noisy Training Data

A regression random forest model taking into account imprecision of the decision tree estimates is proposed. The imprecision stems from conditions of small or noisy training data which may take place in many applications. In fact, a meta-model is proposed to train and to compute optimal weights assigned to decision trees, which control the imprecision in order to get the robust random forest estimates. The imprecision of the tree estimations is defined by means of interval models, for example, by using confidence intervals. The weights are computed by solving a standard quadratic optimization problem with linear constraints. Numerical examples illustrate the proposed robust model which provides outperforming results for noisy and small data in comparison with the standard random forest.
Opportunities and Challenges for Resource Management and Machine Learning Clusters

The practice of collecting big performance data has changed how infrastructure providers model and manage the system in the past decade. There is a methodology shift from domain-knowledge based white-box models, e.g., queueing [1] and simulation[2], to black-box data-driven models, e.g., machine learning. Such a game change for resource management from workload characterization[3], dependability prediction [4,5] to sprinting policy[6], can be seen from major IT infastructure providers, e.g., IBM and Google.
Gated Fusion of Discriminant Features for Caricature Recognition

Caricature recognition is a challenging problem, because there are typically geometric deformations between photographs and caricatures. It is nontrivial to learn discriminant large-margin features. To combat this challenge, we propose a novel framework by using a gated fusion of global and local discriminant features. First, we employ A-Softmax loss to jointly learn angularly discriminant features of the whole face and local facial parts. Besides, we use the convolutional block attention module (CBAM) to further boost the discriminant ability of the learnt features. Next, we use global features as dominant representation and local features as supplemental ones; and propose a gated fusion unit to automatically learn the weighting factors for these local parts and moderate local features correspondingly. Finally, an integration of all these features is used for caricature recognition. Extensive experiments are conducted on the cross-modal face recognition task. Results show that, our method significantly boosts previous state-of-the-art Rank-1 and Rank-10 from 36.27% to 55.29% and from 64.37% to 85.78%, respectively, for caricature-to-photograph (C2P) recognition. Besides, our method achieves a Rank-1 of 60.81% and Rank-10 of 89.26% for photograph-to-caricature (P2C) recognition.
The Idea of D.D. Shamray’s Doctoral Dissertation “Free Printing Houses of the Eighteenth Century (1783—1796)”

The article considers the unpublished heritage of D.D Shamray (1886—1971), book historian, bibliologist, library scientist and bibliographer, employee of the Imperial Public Library (State Public Library named after M.E. Saltykov-Shchedrin, now — The National Library of Russia, NLR), connected with his idea of doctoral thesis on the period of free printing in Russia (1783—1796) in the beginning of 1950s. Archival materials on this topic are stored in the Department of manuscripts of the Russian State Library (RSL) and the Department of archival documents of the NLR. The plan of dissertation “Free Printing Houses of the Eighteenth Century (1783—1796)” and the unpublished work “The New Printing House of the Academy of Sciences, 1758—1783” reveal the idea of D.D. Shamray. These materials show that the scientist intended to pay special attention to the study of social, cultural, political prerequisites for the emergence of “free printing”, including the repertoire of manuscript books of the 18th century, and to highlight the practice of private orders in state printing plants as a prehistory of free printing. D.D. Shamray planned to create “Book chronicle of free printing houses”, understanding it as the compilation of complete bibliography of published products prepared in private printing houses during the period of “free printing”. D.D. Shamray widely used archival sources, mainly the documents of the Archive of the Academy of Sciences (now — St. Petersburg Branch of the Archive of the Russian Academy of Sciences), citing some of them in their entirety. However, the scientist did not reach the level of wide generalization and as a result, most of his texts on this topic remained unpublished. The study of materials on the unrealized plan of D.D. Shamray testifies to the important historiographical significance of the unpublished works for the complete understanding of the history of the scientific process in the field of domestic book studies and the history of book.
Virtual Media Quality Index (W-Index) for Higher Institutions of Education

The simplicity and ease of access of its website, has allowed YouTube to be embraced by the whole world and establish itself as the most prominent form of video sharing on earth. YouTube has become a widely used medium for individuals, corporations, and academic institutions alike. In the current work a W-index has been developed and applied to many academic institutions to evaluate the efficacy of the respective YouTube channel(s). This index was the creative product of the senior author who was inspired by the H-index developed by J.E. Hirsch (2005) to evaluate the productivity and impact of a researcher. The W-index will be used to evaluate the quantity and quality of a University’s channel that is different from the traditional staples that define popularity and video effectiveness on YouTube, such as total views. The methodology used would be to see that if this W-index would correlate well to existing indices used for the evaluation of universities. Eventually, the W-index could serve as an indicator of whether or not a university needs to invest time or money into the development of better videos or more videos for their YouTube channel to maximize its impact on the academic community. A correlation between W-Index and three well-established and well-defined cybermetric rankings; US Rank, Impact Rank, and Excellence Rank, is established and used as the basis for the Windex’s usefulness. The establishment of such a correlation indicates that the W-Index can also be used to evaluate the communication efficacy of individuals, despite the lack of any robust ranking system for individuals. The W-Index serves as a good indicator, based on consistent correlation coefficients among ranking systems analyzed, of a university or individual’s success and communication efficacy. Rankings are useful as single numbers that contribute to decision making, simply because of their simplicity.
Detection and identification of objects on multispectral satellite images

Abstract This article considers the detection of objects on the time sequences of satellite multizone images. Optimal and quasi-optimal detection algorithms are built on the basis of a combination of non-linear double stochastic filters and pseudo-gradient procedures. The analysis of behavior of the synthesized algorithms at processing of the real satellite material under conditions of a priori uncertainty concerning parameters of deformation of the reference image is carried out.
A Hybrid Model for Liver Shape Segmentation with Customized Fast Marching and Improved GMM-EM

This paper describes an approach to segment liver shape from abdominal CT sequences, required by the analysis of liver diseases. A rough segmentation is first conducted via a customized Fast Marching method to obtain an approximate 3D liver region for subsequent procedure. Then, an improvement of GMM-EM algorithm is made to extract the accurate liver region. Experimental results, evaluated on non-tumor series and tumor series of 10 cases, show that the proposed method performs better than several other typical segmentation models in running time and precision.
The Combination of Morphological and Evolutionary Algorithms for Graph-based Pathfinding on Maps with Complex Topologies

One of the difficult problems to solve has always been and still remains the problem of finding a path either in a graphic chart or a graphic maze of large size. The main problem is that traditional algorithms require a lot of time due to combinatorial complexity. At the same time, both classical algorithms based on the search of variants (such as Dijkstra's algorithm, A*, ARA*, D* lite), and stochastic algorithms (ant algorithm, genetic), alongside with algorithms based on morphology (wave) are not always able to achieve the goal. The article proposes a new modification of the path-finding algorithm, which is a hybrid of the following: the morphological operations on graphic chart approach and genetic algorithm having a useful property of elasticity in time. The experiments (both synthetic and real data) have shown the feasibility of the proposed idea and its comparison with the most commonly used algorithms of contemporaneity.
Topological descriptors of philosophical text

The article considers the problem of topological descriptors of a philosophical text. Topological descriptors act as discursive points for the localization of the philosophical text, which allow us to describe its role and place in the production of modern humanitarian knowledge. Three perspectives of the analysis of the philosophical text in the contemporary sociocultural situation are outlined: the perspective of historical and philosophical research, the perspective of cultural research and the perspective of modern humanitarian knowledge. The historical and philosophical perspective from the point of view of topology is described through genre differences between philosophical texts, and also taking into account the differences between philosophical schools, trends, styles of thinking in intellectual history. The perspective of cultural research includes a philosophical text in a wide context of political, social and cultural transformations of modern society, and it becomes possible to talk about social topology. The perspective of modern humanitarian knowledge is analyzed from the perspective of the rehabilitation of philosophical discourse, the need for detailed textual work for the full inclusion of philosophy in the production process of significant social and cultural knowledge. As an original methodological approach, the article describes topological analytics, which is actively used by modern researchers to solve a whole range of issues of localization, description and understanding of the role of a philosophical text in modern humanities. Conclusions are drawn about the prospects of further research in this direction.
A Generic Framework for Collaborative Recommendation in a Scientific Network

Social recommender systems (SRS) become more and more popular as they allow use more information about users and alleviate cold-start problem. Traditional recommender systems have concentrated on information or document retrieval and then were extended with methods for music or movie recommendations. SRS are useful especially in the context of online stores: user can quickly find relevant items and a company can improve its income by recommending additional items.A slightly different situation is in the case of research paper recommendation. Usually, researchers are looking for relevant papers using some search engines. Using a few keywords, one can obtain a list of similar works. Let us consider a situation when a researcher likes to find conference or journal where it is worth to publish. He or she receives many,,calls for papers” but most of them are not correlated with their researcher interests. In this paper we propose a method for journal or conference recommendation based on social community of researchers. We present a method that combines content-based, collaborative and social approaches to find the best place to publish.
Adapted methodology for comprehensive contamination assessment of bottom sediments on the content of various forms of heavy metals

Abstract As a result of long-term studies of bottom sediments of lakes, rivers, ponds and reservoirs of the Republic of Tatarstan, considerable factual material has been accumulated, which enabled the translation of quantitative estimates into qualitative characteristics. This necessitated a comprehensive assessment and generalization of the exceedance of the thresholds set for all metals, similarly to the specific combinatorial water pollution index (SCWPI). At the same time, the authors emphasize the features of such a comprehensive assessment of bottom sediments, and also suggest methods and algorithms for solving emerging problems. We use the method of frequency characteristics of data series of metal content (Cd, Pb, Co, Cu, Ni, Zn, Cr, Mn, Fe) in bottom sediments, score the relevant characteristics, generalize the point estimates and bring them to the appropriate classes of purity. As a result, a method for the integrated assessment of contamination of bottom sediments was developed and tested, which solves the problem of the integral assessment of the quality of bottom sediments in terms of a complex of pollutants using the example of heavy metals. The method is based on the approach of the SCWPI. Therefore, its results are comparable to combinatorial assessments of water quality, which will allow deriving a uniform assessment of the water body as a whole.
A Group-Centric Physical Education Supporting System for Intelligent Campus Application

The concept of intelligent campus has been put forward for many years, aiming to provide high quality services dynamically and proactively for students, teachers and other employees in university in the era of Internet of Things. There exists a phenomenon that the health status of college students is continuously declining, which has aroused public concerns. This phenomenon could be improved via offering intelligent management services to college physical instructors by taking advantage of advanced Internet of Things (IoT) technologies. In this paper, a framework for group-centric physical education supporting system based on wristbands and cloud platform is proposed. The specific methods are divided into three parts based on event streams: IoT nodes networking and configuration before class, real-time health status monitoring and emergency detection in class, and students’ performance and course quality evaluation after class, which provide an overall insight into students’ fitness and exercise condition for the physical teachers. In addition, a prototype system is implemented for teaching test and to prove the feasibility of the proposed methodology, and the comparison of our proposed methods with other systems is also discussed.
A Proposal of Creating Ideal UTAU Voice Based on Voice of the User's Own Key by Interactive Differential Evolution

The following topics are dealt with: learning (artificial intelligence); object detection; computer games; Internet; support vector machines; disasters; emergency services; image sequences; video signal processing; image segmentation.
A Scale-based Interest Operator for Autonomous Robotic Exploration

For a variety of use cases, the utility of autonomous mobile robots is strengthened by a capacity to explore spatial environments with particular focus on objects or phenomena of interest. To generally support such a capacity, an agile, application-agnostic interest operator is constructed to visually guide focused autonomous exploration. An interest operator is proposed that serves to identify unique features in a scene in an application-agnostic manner by maintaining a sort of “short-term memory” and identifying regions that are unique within the context of what has already been ascertained about the scene, not necessarily what is unique or of interest for a given application. The proposed interest operator is particularly suited to render-based mapping and perception, taking advantage of the natural characterization of spaces comprising an environment as free, occupied, and unknown, and the rich, highly-detailed texture information supported in graphical renderings of visual scenes. With focus on two scales of image features, one being driven by discontinuities between surfaces and the other based on variations in texture of surfaces in a region, the proposed interest operator can inform robot sensing and navigation decisions and resource allocation during autonomous exploration. Results from numerical experiments demonstrate the efficacy of the approach.
Website Development of Indonesian Art Higher Education Institutions Historical Archives

Abstract Art Higher Education Institution in Indonesia has been established since 1947, and ever since has developed in different parts of Indonesia. Indonesia as a country with rich culture and arts, has its own history and characteristics regarding its visual arts development. Prominent names in The History of Art Higher Education Institutions in Indonesia includes names, such as Simon Admiraal, Ries Mulder and RJ Katamsi. They had historical account of establishing Universitaire Leergang voor Tekenleraren (FSRD ITB) and ASRI located in Bandung and Yogyakarta respectively. The goal of this research and development is aimed towards information propagation regarding these historical data and information of art higher education institutions in Indonesia. The project was initiated by Creative Arts Department of Telkom University, which also acts as an art higher education institution. The website development methodology went through several phases, which includes data collections of art higher education institutions in Indonesia, qualitative research that includes interviews and observations of key persons, as well as using Website Generation Model methodology in its development. The preliminary results of this research project informs that the website has perform well in key objectives regarding needs, systems and learning process. In the future it is needed to also research similar projects in Indonesia such as online art database like IVAA (Indonesian Visual Art Archive) which originated in Yogyakarta. The preliminary conclusions of currently ongoing research are that it is necessary to build such online database to hold historical data about the subject, and that the visual aspects of the website have the most consideration for the success of this project. The impact of this research for current development is that the research give way to utilizing qualitative research as well as Website Generation Model in developing better and more attracting websites.
Personalized Recommendation Based on Tag Semantics in the Heterogeneous Information Network

Heterogeneous information network (HIN) is widely used in recommendation system because of its superiority in complex information modeling. However, the existing HIN-based methods ignore two issues. First, low-quality information may cause users to be dissatisfied with the recommendation results. Secondly, HIN-based recommendations are difficult to predict the user’s attitude toward the item. Therefore, this paper proposes two improvement strategies: (1) propose a semantic information filtering strategy to filter low-quality information and improve recommendation efficiency; (2) integrate tag information into HIN-based recommendation system to achieve personalization recommend. This paper verifies the validity of the proposed model on two real data sets.
Robust weighted regression via PAELLA sample weights

This paper reports the usage of the occurrence vector provided by the PAELLA algorithm in the context of robust regression. PAELLA was originally conceived as an outlier detection and data cleaning technique. A novel approach is to use this algorithm not for discarding outliers but to generate information related to the reliability of the observations recorded in the dataset. This approach proves to provide successful results when compared to traditional common practice such as outlier removal. A set of experiments using a contrived difficult artificial dataset are described using both neural networks and classical polynomial fitting. Finally, a successful comparison of our approach to two state-of-the-art algorithms proves the benefits of using the PAELLA algorithm in the context of robust regression.
Non-institutional learning technologies, risks and responsibilities: a critical discourse analysis of university artefacts

Non-institutional technologies include external or third-party technologies that are not officially sanctioned or supported by higher education institutions (HEIs) but may be used by staff for educational purposes. These include free, open-source and open-access technologies such as social media sites, apps and online services. The literature identifies a number of risks and ethical considerations when using digital technologies, such as security, safety, privacy and legal compliance (Common Sense&nbsp;n.d.). This study analyses institutional artefacts, including policy and guidance documents, to explore how institutions are addressing the risks of educational technologies identified throughout the literature. Critical discourse analysis was conducted on nine artefacts, obtained from seven UK HEIs. The study found that institutional policies and guidance documents do not sufficiently address some of the key risks identified in the literature (e.g. security risks), nor consider the ethical issues emerging from the use of profit-making educational products. Users of these technologies (including teaching staff) are assigned a broad range of complex and potentially time-consuming responsibilities concerning the evaluation, selection and operation of these technologies. For example, to ensure compliance with data protection legislation, however, no artefact stated how this should be achieved. The study therefore identifies significant inadequacies in institutional policies and guidelines, and questions whether appropriate quality assurance processes and safeguards are in place when non-institutional technologies are used for higher education.