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  1. Gesprochenes Recht?
    Author: Csármán, Magdalena
    Published: 2021
    Publisher:  KOMINFORM, Verein für Kommunikation u. Information, Wien

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    Source: Union catalogues
    Language: German
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Juridikum / Hrsg.: Context - Verein für Freie Studien und Brauchbare Informationen; Wien, 2021; Heft 4 (13.12.2021), Seite 447-454
    Subjects: Recht; Gesprochenes Wort; Mündlichkeit; Rechtswirkung; ; Österreich; COVID-19; Pandemie; Verordnung; Auslegung; Rechtsgeltung; ; Rechtsstaat; Verwaltungsrecht; Österreich; Rechtsprechung;
  2. EU-VK-Handelsabkommen TCA: Streitbeilegung EU-rechtskonform?
    Author: Brauneck, Jens
    Published: 2021
    Publisher:  Beck, München [u.a.]

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    Source: Union catalogues
    Language: German
    Media type: Article (journal)
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    Parent title: Enthalten in: Europäische Zeitschrift für Wirtschaftsrecht; München [u.a.], 2021; (2021) Heft 7, Seite 291-299
    Subjects: Europäische Union; Großbritannien; Brexit; Handelsabkommen; Auslegung; Vertragspartei; ; Europäischer Gerichtshof; Rechtsprechung;
  3. Hirofumi Hosokawa: Zeitungssprache und Mündlichkeit. Frankfurt, M.: Lang-Ed., 2014
    Author: Nitta, Haruo
    Published: 2021

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    Source: Online Contents Comparative Literature
    Language: English
    Media type: Article (journal); Review
    Format: Print
    Parent title: Enthalten in: Journal of literary semantics; Berlin [u.a.] : Mouton De Gruyter, 1972-; Band 50, Heft 1 (2021), Seite 208-213

  4. Damaris Nübling: Historische Sprachwissenschaft des Deutschen. Tübingen: Narr, 2013
    Author: Kujiraoka, Satsuki
    Published: 2021

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    Source: Online Contents Comparative Literature
    Language: English
    Media type: Article (journal); Review
    Format: Print
    Parent title: Enthalten in: Journal of literary semantics; Berlin [u.a.] : Mouton De Gruyter, 1972-; Band 50, Heft 1 (2021), Seite 226-227

  5. Claudia Telschow: Die Adjektiv-Adverb-Abgrenzung im Deutschen. Berlin: De Gruyter, 2014
    Author: Iguchi, Shinichi
    Published: 2021

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    Source: Online Contents Comparative Literature
    Language: English
    Media type: Article (journal); Review
    Format: Print
    Parent title: Enthalten in: Journal of literary semantics; Berlin [u.a.] : Mouton De Gruyter, 1972-; Band 50, Heft 1 (2021), Seite 227-228

  6. Im Graubereich der Macht : Müller, Tieck und Goethe über Staatskredit und Papiergeld (mit einem Seitenblick auf Chamisso)
    Author: Bergengruen, Maximilian
    Published: 2021

    Was passiert nun – diese Frage soll im Mittelpunkt dieses Aufsatzes stehen –, wenn auch der Souverän eine Geldschuld trägt, und zwar gegenüber seinen – ihm in Form von verzinsten Nationalkrediten oder Papiergeld borgenden – Bürgern? Die Antwort, die... more

     

    Was passiert nun – diese Frage soll im Mittelpunkt dieses Aufsatzes stehen –, wenn auch der Souverän eine Geldschuld trägt, und zwar gegenüber seinen – ihm in Form von verzinsten Nationalkrediten oder Papiergeld borgenden – Bürgern? Die Antwort, die in den geldtheoretischen Texten Müllers sowie den Dramen Tiecks und Goethes gegeben wird, lässt sich auf zwei Ebenen skizzieren: Erstens gilt, dass papiernes "Geld" nichts anderes als der ökonomische Ausdruck für das "Bedürfniß der Vereinigung oder für den Staat" ist. Es lässt sich also eine wechselseitige Verpflichtung konstatieren: Der Einzelne zahlt seine Schuld als Teilhaber dieses Staates in Form von Abgaben und Steuern; gleichzeitig macht er diesen Staat überhaupt erst zu einem Staat, indem er ihm bzw. seinem Oberhaupt, zum Beispiel in Form von Papiergeld, Kredit gibt.

     
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    Source: BASE Selection for Comparative Literature
    Language: German
    Media type: Article (journal)
    Format: Online
    DDC Categories: 830
    Subjects: Kredit <Motiv>; Geld <Motiv>; Müller; Adam Heinrich; Tieck; Ludwig; Goethe; Johann Wolfgang von
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  7. Comparing the Safety and Efficacy of Microwave Ablation Using Thermosphere TM Technology versus Radiofrequency Ablation for Hepatocellular Carcinoma: A Propensity Score-Matched Analysis
    Author: Hidekatsu Kuroda; Tomoaki Nagasawa; Yudai Fujiwara; Hiroki Sato; Tamami Abe; Yohei Kooka; Kei Endo; Takayoshi Oikawa; Kei Sawara; Yasuhiro Takikawa
    Published: 2021
    Publisher:  MDPI AG

    There is limited information regarding the oncological benefits of microwave ablation using Thermosphere TM technology for hepatocellular carcinoma. This study compared the overall survival and recurrence-free survival outcomes among patients with... more

     

    There is limited information regarding the oncological benefits of microwave ablation using Thermosphere TM technology for hepatocellular carcinoma. This study compared the overall survival and recurrence-free survival outcomes among patients with hepatocellular carcinoma after microwave ablation using Thermosphere TM technology and after radiofrequency ablation. Between December 2017 and August 2020, 410 patients with hepatocellular carcinoma (a single lesion that was ≤5 cm or ≤3 lesions that were ≤3 cm) underwent ablation at our institution. Propensity score matching identified 150 matched pairs of patients with well-balanced characteristics. The microwave ablation and radiofrequency ablation groups had similar overall survival rates at 1 year (99.3% vs. 98.2%) and at 2 years (88.4% vs. 87.5%) ( p = 0.728), as well as similar recurrence-free survival rates at 1 year (81.1% vs. 76.2%) and at 2 years (60.5% vs. 62.1%) ( p = 0.492). However, the microwave ablation group had a significantly lower mean number of total insertions (1.22 ± 0.49 vs. 1.59 ± 0.94; p < 0.0001). This retrospective study revealed no significant differences in the overall survival and recurrence-free survival outcomes after microwave ablation or radiofrequency ablation. However, we recommend microwave ablation for hepatocellular carcinoma tumors with a diameter of >2 cm based on the lower number of insertions.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Cancers, Vol 13, Iss 1295, p 1295 (2021)
    Subjects: hepatocellular carcinoma; microwave ablation; radiofrequency ablation; Neoplasms. Tumors. Oncology. Including cancer and carcinogens
  8. MStractor: R Workflow Package for Enhancing Metabolomics Data Pre-Processing and Visualization
    Author: Luca Nicolotti; Jeremy Hack; Markus Herderich; Natoiya Lloyd
    Published: 2021
    Publisher:  MDPI AG

    Untargeted metabolomics experiments for characterizing complex biological samples, conducted with chromatography/mass spectrometry technology, generate large datasets containing very complex and highly variable information. Many data-processing... more

     

    Untargeted metabolomics experiments for characterizing complex biological samples, conducted with chromatography/mass spectrometry technology, generate large datasets containing very complex and highly variable information. Many data-processing options are available, however, both commercial and open-source solutions for data processing have limitations, such as vendor platform exclusivity and/or requiring familiarity with diverse programming languages. Data processing of untargeted metabolite data is a particular problem for laboratories that specialize in non-routine mass spectrometry analysis of diverse sample types across humans, animals, plants, fungi, and microorganisms. Here, we present MStractor, an R workflow package developed to streamline and enhance pre-processing of metabolomics mass spectrometry data and visualization. MStractor combines functions for molecular feature extraction with user-friendly dedicated GUIs for chromatographic and mass spectromerty (MS) parameter input, graphical quality-control outputs, and descriptive statistics. MStractor performance was evaluated through a detailed comparison with XCMS Online. The MStractor package is freely available on GitHub at the MetabolomicsSA repository.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Metabolites, Vol 11, Iss 492, p 492 (2021)
    Subjects: metabolomics; data analysis; pre-processing; R programming language; LC/MS; Microbiology
  9. An Efficient Gait Recognition Method for Known and Unknown Covariate Conditions
    Author: Maryam Bukhari; Khalid Bashir Bajwa; Saira Gillani; Muazzam Maqsood; Mehr Yahya Durrani; Irfan Mehmood; Hassan Ugail; Seungmin Rho
    Published: 2021
    Publisher:  IEEE

    Gait is a unique non-invasive biometric form that can be utilized to effectively recognize persons, even when they prove to be uncooperative. Computer-aided gait recognition systems usually use image sequences without considering covariates like... more

     

    Gait is a unique non-invasive biometric form that can be utilized to effectively recognize persons, even when they prove to be uncooperative. Computer-aided gait recognition systems usually use image sequences without considering covariates like clothing and possessions of carrier bags whilst on the move. Similarly, in gait recognition, there may exist unknown covariate conditions that may affect the training and testing conditions for a given individual. Consequently, common techniques for gait recognition and measurement require a degree of intervention leading to the introduction of unknown covariate conditions, and hence this significantly limits the practical use of the present gait recognition and analysis systems. To overcome these key issues, we propose a method of gait analysis accounting for both known and unknown covariate conditions. For this purpose, we propose two methods, i.e., a Convolutional Neural Network (CNN) based gait recognition and a discriminative features-based classification method for unknown covariate conditions. The first method can handle known covariate conditions efficiently while the second method focuses on identifying and selecting unique covariate invariant features from the gallery and probe sequences. The feature set utilized here includes Local Binary Patterns (LBP), Histogram of Oriented Gradients (HOG), and Haralick texture features. Furthermore, we utilize the Fisher Linear Discriminant Analysis for dimensionality reduction and selecting the most discriminant features. Three classifiers, namely Random Forest, Support Vector Machine (SVM), and Multilayer Perceptron are used for gait recognition under strict unknown covariate conditions. We evaluated our results using CASIA and OUR-ISIR datasets for both clothing and speed variations. As a result, we report that on average we obtain an accuracy of 90.32% for the CASIA dataset with unknown covariates and similarly performed excellently on the ISIR dataset. Therefore, our proposed method outperforms existing methods for ...

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: IEEE Access, Vol 9, Pp 6465-6477 (2021)
    Subjects: Gait recognition; covariate conditions; discriminative feature learning; FLDA; Electrical engineering. Electronics. Nuclear engineering
  10. Comparison of Feature Extraction Methods for Physiological Signals for Heat-Based Pain Recognition
    Author: Philip Gouverneur; Frédéric Li; Wacław M. Adamczyk; Tibor M. Szikszay; Kerstin Luedtke; Marcin Grzegorzek
    Published: 2021
    Publisher:  MDPI AG

    While even the most common definition of pain is under debate, pain assessment has remained the same for decades. But the paramount importance of precise pain management for successful healthcare has encouraged initiatives to improve the way pain is... more

     

    While even the most common definition of pain is under debate, pain assessment has remained the same for decades. But the paramount importance of precise pain management for successful healthcare has encouraged initiatives to improve the way pain is assessed. Recent approaches have proposed automatic pain evaluation systems using machine learning models trained with data coming from behavioural or physiological sensors. Although yielding promising results, machine learning studies for sensor-based pain recognition remain scattered and not necessarily easy to compare to each other. In particular, the important process of extracting features is usually optimised towards specific datasets. We thus introduce a comparison of feature extraction methods for pain recognition based on physiological sensors in this paper. In addition, the PainMonit Database (PMDB), a new dataset including both objective and subjective annotations for heat-induced pain in 52 subjects, is introduced. In total, five different approaches including techniques based on feature engineering and feature learning with deep learning are evaluated on the BioVid and PMDB datasets. Our studies highlight the following insights: (1) Simple feature engineering approaches can still compete with deep learning approaches in terms of performance. (2) More complex deep learning architectures do not yield better performance compared to simpler ones. (3) Subjective self-reports by subjects can be used instead of objective temperature-based annotations to build a robust pain recognition system.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Sensors, Vol 21, Iss 4838, p 4838 (2021)
    Subjects: pain recognition; machine learning; deep learning; physiological signals; pain perception; Chemical technology
  11. Continuous stage stochastic Runge–Kutta methods
    Author: Xuan Xin; Wendi Qin; Xiaohua Ding
    Published: 2021
    Publisher:  SpringerOpen

    Abstract In this work, a version of continuous stage stochastic Runge–Kutta (CSSRK) methods is developed for stochastic differential equations (SDEs). First, a general order theory of these methods is established by the theory of stochastic B-series... more

     

    Abstract In this work, a version of continuous stage stochastic Runge–Kutta (CSSRK) methods is developed for stochastic differential equations (SDEs). First, a general order theory of these methods is established by the theory of stochastic B-series and multicolored rooted tree. Then the proposed CSSRK methods are applied to three special kinds of SDEs and the corresponding order conditions are derived. In particular, for the single integrand SDEs and SDEs with additive noise, we construct some specific CSSRK methods of high order. Moreover, it is proved that with the help of different numerical quadrature formulas, CSSRK methods can generate corresponding stochastic Runge–Kutta (SRK) methods which have the same order. Thus, some efficient SRK methods are induced. Finally, some numerical experiments are presented to demonstrate those theoretical results.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Advances in Difference Equations, Vol 2021, Iss 1, Pp 1-22 (2021)
    Subjects: Stochastic differential equations; Continuous stage stochastic Runge–Kutta methods; B-series; Mathematics
  12. Retinal OCT Texture Analysis for Differentiating Healthy Controls from Multiple Sclerosis (MS) with/without Optic Neuritis
    Author: Hamidreza Dehghan Tazarjani; Zahra Amini; Rahele Kafieh; Fereshteh Ashtari; Erfan Sadeghi
    Published: 2021
    Publisher:  Hindawi Limited

    Multiple sclerosis (MS) is an inflammatory disease damaging the myelin sheath in the central and peripheral nervous system in the brain and spinal cord. Optic Neuritis (ON) is one of the most prevalent ocular demonstrations of MS. The current... more

     

    Multiple sclerosis (MS) is an inflammatory disease damaging the myelin sheath in the central and peripheral nervous system in the brain and spinal cord. Optic Neuritis (ON) is one of the most prevalent ocular demonstrations of MS. The current diagnosis protocol for MS is MRI, but newer modalities like Optical Coherence Tomography (OCT) are already of interest in early detection and progression analysis. OCT reveals the symptoms of MS in the Central Nervous System (CNS) through cross-sectional images from neural retinal layers. Previous works on OCT were mostly focused on the thickness of retinal layers; however, texture features seem also to have information in this regard. In this research, we introduce a new pipeline that constructs layer-stacked (LS) images containing data from each specific layer. A variety of texture features are then extracted from LS images to differentiate between healthy controls and ON/None-ON MS cases. Furthermore, the definition of texture extraction methods is tailored for this application. After performing a vast survey on available texture analysis methods, a treasury of powerful features is collected in this paper. As a primary work, this paper shows the ability of such features in the diagnosis of HC and MS (ON and None-ON) cases. Our findings show that the texture features are powerful to diagnose MS cases. Furthermore, adding information of conventional thickness values to texture features improves considerably the discrimination between most of the target groups including HC vs. MS, HC vs. MS-None-ON, and HC vs. MS-ON.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: BioMed Research International, Vol 2021 (2021)
    Subjects: Medicine; R
  13. LinkedImm: a linked data graph database for integrating immunological data
    Author: Syed Ahmad Chan Bukhari; Shrikant Pawar; Jeff Mandell; Steven H. Kleinstein; Kei-Hoi Cheung
    Published: 2021
    Publisher:  BMC

    Abstract Background Many systems biology studies leverage the integration of multiple data types (across different data sources) to offer a more comprehensive view of the biological system being studied. While SQL (Structured Query Language)... more

     

    Abstract Background Many systems biology studies leverage the integration of multiple data types (across different data sources) to offer a more comprehensive view of the biological system being studied. While SQL (Structured Query Language) databases are popular in the biomedical domain, NoSQL database technologies have been used as a more relationship-based, flexible and scalable method of data integration. Results We have created a graph database integrating data from multiple sources. In addition to using a graph-based query language (Cypher) for data retrieval, we have developed a web-based dashboard that allows users to easily browse and plot data without the need to learn Cypher. We have also implemented a visual graph query interface for users to browse graph data. Finally, we have built a prototype to allow the user to query the graph database in natural language. Conclusion We have demonstrated the feasibility and flexibility of using a graph database for storing and querying immunological data with complex biological relationships. Querying a graph database through such relationships has the potential to discover novel relationships among heterogeneous biological data and metadata.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: BMC Bioinformatics, Vol 22, Iss S9, Pp 1-14 (2021)
    Subjects: Ontology; Knowledgebase; Graph database; Immunology; Influenza vaccine; Computer applications to medicine. Medical informatics; Biology (General)
  14. Towards an Engagement-Aware Attentive Artificial Listener for Multi-Party Interactions
    Author: Catharine Oertel; Patrik Jonell; Dimosthenis Kontogiorgos; Kenneth Funes Mora; Jean-Marc Odobez; Joakim Gustafson
    Published: 2021
    Publisher:  Frontiers Media S.A.

    Listening to one another is essential to human-human interaction. In fact, we humans spend a substantial part of our day listening to other people, in private as well as in work settings. Attentive listening serves the function to gather information... more

     

    Listening to one another is essential to human-human interaction. In fact, we humans spend a substantial part of our day listening to other people, in private as well as in work settings. Attentive listening serves the function to gather information for oneself, but at the same time, it also signals to the speaker that he/she is being heard. To deduce whether our interlocutor is listening to us, we are relying on reading his/her nonverbal cues, very much like how we also use non-verbal cues to signal our attention. Such signaling becomes more complex when we move from dyadic to multi-party interactions. Understanding how humans use nonverbal cues in a multi-party listening context not only increases our understanding of human-human communication but also aids the development of successful human-robot interactions. This paper aims to bring together previous analyses of listener behavior analyses in human-human multi-party interaction and provide novel insights into gaze patterns between the listeners in particular. We are investigating whether the gaze patterns and feedback behavior, as observed in the human-human dialogue, are also beneficial for the perception of a robot in multi-party human-robot interaction. To answer this question, we are implementing an attentive listening system that generates multi-modal listening behavior based on our human-human analysis. We are comparing our system to a baseline system that does not differentiate between different listener types in its behavior generation. We are evaluating it in terms of the participant’s perception of the robot, his behavior as well as the perception of third-party observers.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Frontiers in Robotics and AI, Vol 8 (2021)
    Subjects: multi-party interactions; non-verbal behaviors; eye-gaze patterns; head gestures; human-robot interaction; artificial listener; Mechanical engineering and machinery; Electronic computers. Computer science
  15. Multi‐modal meta‐analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor
    Author: Alok Jaiswal; Prson Gautam; Elina A Pietilä; Sanna Timonen; Nora Nordström; Yevhen Akimov; Nina Sipari; Ziaurrehman Tanoli; Thomas Fleischer; Kaisa Lehti; Krister Wennerberg; Tero Aittokallio
    Published: 2021
    Publisher:  Wiley

    Abstract Molecular and functional profiling of cancer cell lines is subject to laboratory‐specific experimental practices and data analysis protocols. The current challenge therefore is how to make an integrated use of the omics profiles of cancer... more

     

    Abstract Molecular and functional profiling of cancer cell lines is subject to laboratory‐specific experimental practices and data analysis protocols. The current challenge therefore is how to make an integrated use of the omics profiles of cancer cell lines for reliable biological discoveries. Here, we carried out a systematic analysis of nine types of data modalities using meta‐analysis of 53 omics studies across 12 research laboratories for 2,018 cell lines. To account for a relatively low consistency observed for certain data modalities, we developed a robust data integration approach that identifies reproducible signals shared among multiple data modalities and studies. We demonstrated the power of the integrative analyses by identifying a novel driver gene, ECHDC1, with tumor suppressive role validated both in breast cancer cells and patient tumors. The multi‐modal meta‐analysis approach also identified synthetic lethal partners of cancer drivers, including a co‐dependency of PTEN deficient endometrial cancer cells on RNA helicases.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Molecular Systems Biology, Vol 17, Iss 3, Pp n/a-n/a (2021)
    Subjects: cancer driver; data integration; multi‐omics data; reproducibility; synthetic lethality; Biology (General); Medicine (General)
  16. Graph of graphs analysis for multiplexed data with application to imaging mass cytometry.
    Author: Ya-Wei Eileen Lin; Tal Shnitzer; Ronen Talmon; Franz Villarroel-Espindola; Shruti Desai; Kurt Schalper; Yuval Kluger
    Published: 2021
    Publisher:  Public Library of Science (PLoS)

    Imaging Mass Cytometry (IMC) combines laser ablation and mass spectrometry to quantitate metal-conjugated primary antibodies incubated in intact tumor tissue slides. This strategy allows spatially-resolved multiplexing of dozens of simultaneous... more

     

    Imaging Mass Cytometry (IMC) combines laser ablation and mass spectrometry to quantitate metal-conjugated primary antibodies incubated in intact tumor tissue slides. This strategy allows spatially-resolved multiplexing of dozens of simultaneous protein targets with 1μm resolution. Each slide is a spatial assay consisting of high-dimensional multivariate observations (m-dimensional feature space) collected at different spatial positions and capturing data from a single biological sample or even representative spots from multiple samples when using tissue microarrays. Often, each of these spatial assays could be characterized by several regions of interest (ROIs). To extract meaningful information from the multi-dimensional observations recorded at different ROIs across different assays, we propose to analyze such datasets using a two-step graph-based approach. We first construct for each ROI a graph representing the interactions between the m covariates and compute an m dimensional vector characterizing the steady state distribution among features. We then use all these m-dimensional vectors to construct a graph between the ROIs from all assays. This second graph is subjected to a nonlinear dimension reduction analysis, retrieving the intrinsic geometric representation of the ROIs. Such a representation provides the foundation for efficient and accurate organization of the different ROIs that correlates with their phenotypes. Theoretically, we show that when the ROIs have a particular bi-modal distribution, the new representation gives rise to a better distinction between the two modalities compared to the maximum a posteriori (MAP) estimator. We applied our method to predict the sensitivity to PD-1 axis blockers treatment of lung cancer subjects based on IMC data, achieving 97.3% average accuracy on two IMC datasets. This serves as empirical evidence that the graph of graphs approach enables us to integrate multiple ROIs and the intra-relationships between the features at each ROI, giving rise to an informative ...

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: PLoS Computational Biology, Vol 17, Iss 3, p e1008741 (2021)
    Subjects: Biology (General)
  17. Multi-Perspective Attention Network for Fast Temporal Moment Localization
    Author: Jungkyoo Shin; Jinyoung Moon
    Published: 2021
    Publisher:  IEEE

    Temporal moment localization (TML) aims to retrieve the temporal interval for a moment semantically relevant to a sentence query. This is challenging because it requires understanding a video, a sentence, and the relationship between them. Existing... more

     

    Temporal moment localization (TML) aims to retrieve the temporal interval for a moment semantically relevant to a sentence query. This is challenging because it requires understanding a video, a sentence, and the relationship between them. Existing TML methods have shown impressive performances by modeling interactions between videos and sentences using fine-grained techniques. However, these fine-grained techniques require a high computational overhead, making them impractical. This work proposes an effective and efficient multi-perspective attention network for temporal moment localization. Inspired by the way humans understand an image from multiple perspectives and different contexts, we devise a novel multi-perspective attention mechanism consisting of perspective attention and multi-perspective modal interactions. Specifically, a perspective attention layer based on multi-head attention takes two memory sequences, one as the base and the other as the reference memory, as inputs. Perspective attention assesses the two different memories, models the relationship, and encourages the base memory to focus on features related to the reference memory, providing an understanding of the base memory from the perspective of the reference memory. Furthermore, multi-perspective modal interactions model the complex relationship between a video and sentence query, and obtain the modal-interacted memory, consisting of a visual feature that selectively learned query-related information. Similar to the heavyweight fine-grained TML methods, the proposed network obtains the accurate complex relationship while being lightweight like coarse-grained TML methods. We also adopt a fast action recognition network to efficiently extract visual features, which reduce the computational overhead. Through experiments on three TML benchmark datasets, we demonstrate the effectiveness and efficiency of the proposed network.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: IEEE Access, Vol 9, Pp 116962-116972 (2021)
    Subjects: Cross-modal interaction; fast temporal moment localization; temporal moment localization; and temporal sentence grounding; Electrical engineering. Electronics. Nuclear engineering
  18. P2V-RCNN: Point to Voxel Feature Learning for 3D Object Detection From Point Clouds
    Author: Jiale Li; Yu Sun; Shujie Luo; Ziqi Zhu; Hang Dai; Andrey S. Krylov; Yong Ding; Ling Shao
    Published: 2021
    Publisher:  IEEE

    The most recent 3D object detectors for point clouds rely on the coarse voxel-based representation rather than the accurate point-based representation due to a higher box recall in the voxel-based Region Proposal Network (RPN). However, the detection... more

     

    The most recent 3D object detectors for point clouds rely on the coarse voxel-based representation rather than the accurate point-based representation due to a higher box recall in the voxel-based Region Proposal Network (RPN). However, the detection accuracy is severely restricted by the information loss of pose details in the voxels. Different from considering the point cloud as voxel or point representation only, we propose a point-to-voxel feature learning approach to voxelize the point cloud with both the point-wise semantic and local spatial features, which maintains the voxel-wise features to build the high-recall voxel-based RPN and also provides the accurate point-wise features for refining the detection results. Another difficulty in object detection for point cloud is that the visible part varies a lot against the full view of object because of the perspective issues in data acquisition. To address this, we propose an attentive corner aggregation module to attentively aggregate the features of local point cloud surrounding a 3D proposal from the perspectives of eight corners in the proposal 3D bounding box. The experimental results on the competitive KITTI 3D object detection benchmark show that the proposed method achieves state-of-the-art performance.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: IEEE Access, Vol 9, Pp 98249-98260 (2021)
    Subjects: point clouds; attention mechanism; autonomous driving; Electrical engineering. Electronics. Nuclear engineering
  19. Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding
    Author: Martin J. Pearson; Shirin Dora; Oliver Struckmeier; Thomas C. Knowles; Ben Mitchinson; Kshitij Tiwari; Ville Kyrki; Sander Bohte; Cyriel M.A. Pennartz
    Published: 2021
    Publisher:  Frontiers Media S.A.

    Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining information from different sensory sources promotes robustness and accuracy of place... more

     

    Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining information from different sensory sources promotes robustness and accuracy of place recognition. However, mismatch in data registration, dimensionality, and timing between modalities remain challenging problems in multisensory place recognition. Spurious data generated by sensor drop-out in multisensory environments is particularly problematic and often resolved through adhoc and brittle solutions. An effective approach to these problems is demonstrated by animals as they gracefully move through the world. Therefore, we take a neuro-ethological approach by adopting self-supervised representation learning based on a neuroscientific model of visual cortex known as predictive coding. We demonstrate how this parsimonious network algorithm which is trained using a local learning rule can be extended to combine visual and tactile sensory cues from a biomimetic robot as it naturally explores a visually aliased environment. The place recognition performance obtained using joint latent representations generated by the network is significantly better than contemporary representation learning techniques. Further, we see evidence of improved robustness at place recognition in face of unimodal sensor drop-out. The proposed multimodal deep predictive coding algorithm presented is also linearly extensible to accommodate more than two sensory modalities, thereby providing an intriguing example of the value of neuro-biologically plausible representation learning for multimodal navigation.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Frontiers in Robotics and AI, Vol 8 (2021)
    Subjects: predictive coding; multisensory integration; place recognition; sensory reconstruction; whisker tactile; Mechanical engineering and machinery; Electronic computers. Computer science
  20. Video recorder memory calculation of video surveillance system
    Author: O.F.; T.M.; O.V.; V.V.; D.S.; S.M.
    Published: 2021
    Publisher:  Zhytomyr Polytechnic State University

    This article analyzes modern video compression formats, presents and substantiates the algorithm for calculating the required volume of the DVR to allow storage of video surveillance systems for the required period, provides a procedure for selecting... more

     

    This article analyzes modern video compression formats, presents and substantiates the algorithm for calculating the required volume of the DVR to allow storage of video surveillance systems for the required period, provides a procedure for selecting a hard drive in terms of forms of the drive factor, its power consumption and disk speed. When designing modern video surveillance systems, it is necessary to take into account a significant number of factors. The main ones are a type of video cameras, their number, video compression format, image quality, frame activity, shelf life, drive reliability. The advantage of the video surveillance system is the ability to store video data for the required period with the ability to view them. The storage device uses a SD memory card on the camcorder, a storage device in the video recorder, cloud technologies. This article discusses how to save data to the hard disk of the DVR. To date, both analogue and digital or IP video cameras have become widely used, which differ in the principles of video signal generation and network connectivity. The number of camcorders is determined by the characteristics and parameters of the protected object. Every modern IP camcorder supports several data compression formats, which differ in the principles of operation, compression ratio, image quality, and for analogue camcorders compression is performed in the DVR. These factors ultimately affect the total video memory required. In addition, it is important to ensure the reliability of the drive, especially to ensure the monitoring of important objects. Keywords: DVR; video camera; video compression format; codec; drive; video surveillance system.

     
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    Source: BASE Selection for Comparative Literature
    Language: English; Ukrainian
    Media type: Article (journal)
    Format: Online
    Parent title: Технічна інженерія, Vol 1, Iss 87, Pp 104-109 (2021)
    Subjects: Engineering (General). Civil engineering (General)
  21. ATJ Matrices, tools for predicting the validity of a scientific result in Physical Culture/Matrices ATJ, herramientas para pronosticar la validez de un resultado científico en la Cultura Física
    Author: Ana María Morales Ferrer; Tania Ivette Hernández Echevarría; Janet Otero Brande
    Published: 2021
    Publisher:  Universidad de Pinar del Río "Hermanos Saíz Montes de Oca"

    The methods of prognosis are currently used to estimate the occurrence of an expected result, ie, offer the probability of presentation of a quality or process, however, its use is still insufficient in the context of physical culture, so provide a... more

     

    The methods of prognosis are currently used to estimate the occurrence of an expected result, ie, offer the probability of presentation of a quality or process, however, its use is still insufficient in the context of physical culture, so provide a new method and its application methodology, is important as a qualitative filtering process. The aim of this article is to present the ATJ matrices as tools for the prognosis of the validity of a scientific result in Physical Culture. To achieve it, methods such as: opinion poll, unstructured interview, analytical-synthetic, inductive-deductive, analysis of bibliographic sources, systemic-structural-functional, specialists' criteria and statistical-mathematical were used. As a preliminary result, it is possible to obtain a matrix arrangement called ATJ, where four matrices that respond to dimensions are declared; each one with its respective indicators and valuation scales that make it possible to obtain a final evaluation criterion. The procedure provided to the researcher for the application of the matrix arrangement is easy to understand and enables qualitative work to obtain the expected result.

     
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    Source: BASE Selection for Comparative Literature
    Language: Spanish
    Media type: Article (journal)
    Format: Online
    Parent title: Podium, Vol 16, Iss 1, Pp 17-30 (2021)
    Subjects: matrices atj; pronóstico de validez; Sports
  22. Dataset of Bessel function Jn maxima and minima to 600 orders and 10000 extrema
    Author: Nicholas A. Mecholsky; Sepideh Akhbarifar; Werner Lutze; Marek Brandys; Ian L. Pegg
    Published: 2021
    Publisher:  Elsevier

    Bessel functions of the first kind are ubiquitous in the sciences and engineering in solutions to cylindrical problems including electrostatics, heat flow, and the Schrödinger equation. The roots of the Bessel functions are often quoted and... more

     

    Bessel functions of the first kind are ubiquitous in the sciences and engineering in solutions to cylindrical problems including electrostatics, heat flow, and the Schrödinger equation. The roots of the Bessel functions are often quoted and calculated, but the maxima and minima for each Bessel function, used to match Neumann boundary conditions, have not had the same treatment. Here we compute 10000 extrema for the first 600 orders of the Bessel function J. To do this, we employ an adaptive root solver bounded by the roots of the Bessel function and solve to an accuracy of 10−19. We compare with the existing literature (to 30 orders and 5 maxima and minima) and the results match exactly. It is hoped that these data provide values needed for orthogonal function expansions and numerical expressions including the calculation of geometric correction factors in the measurement of resistivity of materials, as is done in the original paper using these data.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Data in Brief, Vol 39, Iss , Pp 107508- (2021)
    Subjects: Bessel functions; GCF; Extrema; Minimum; Maximum; Computer applications to medicine. Medical informatics; Science (General)
  23. Problemy odbioru i odbiorcy w pracach Jurija Łotmana: część 2
    = The problems of reception and recipient in Yuri Lotman's works: part 2
    Author: Żyłko, Bogusław
    Published: 2021

    Location:
    Hessisches BibliotheksInformationsSystem hebis
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    Source: Online Contents Comparative Literature
    Language: Polish
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Acta neophilologica; Olsztyn : Wydawnictwo UWM, 1999-; Band 23, Heft 2 (2021), Seite 95-102

  24. "Poemat o zagładzie Lizbony" (1755) i "Kandyd" (1759) czyli Wolter wobec Leibniza
    = Poem on the Lisbon Disaster (1755) and Candide (1759), or Voltaire versus Leibniz
    Author: Niedziela, Mateusz
    Published: 2021

    Location:
    Hessisches BibliotheksInformationsSystem hebis
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    Source: Online Contents Comparative Literature
    Language: Polish
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Acta neophilologica; Olsztyn : Wydawnictwo UWM, 1999-; Band 23, Heft 2 (2021), Seite 133-146

  25. Wewnętrzna podróż do Demiana - archetypy jungowskie w "Demianie" Hermanna Hessego
    = Inner journey towards Demian: Jungian archetypes in Hermann Hesse's "Demian"
    Author: Szyszka, Kamila
    Published: 2021

    Location:
    Hessisches BibliotheksInformationsSystem hebis
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    Source: Online Contents Comparative Literature
    Language: Polish
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Acta neophilologica; Olsztyn : Wydawnictwo UWM, 1999-; Band 23, Heft 2 (2021), Seite 177-194