cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
COINS: ContinuOus IntegratioN in wirelesS technology development
Creators: name: Vučnik, Matevž
name: Šolc, Tomaž
name: Gregorc, Urban
name: Hrovat, Andrej
name: Bregar, Klemen
name: Smolnikar, Miha
name: Mohorčič, Mihael
name: Fortuna, Carolina
Publisher: name: arXiv
Year: 2018
Subjects: subject: Networking and Internet Architecture (cs.NI)
subject: FOS: Computer and information sciences

description: Network testing plays an important role in the iterative process of developing new communication protocols and algorithms. However, test environments have to keep up with the evolution of technology and require continuous update and redesign. In this paper, we propose COINS, a framework that can be used by wireless technology developers to enable continuous integration (CI) practices in their testbed infrastructure. As a proof-of-concept, we provide a reference architecture and implementation of COINS for controlled testing of multi-technology 5G Machine Type Communication (MTC) networks. The implementation upgrades an existing wireless experimentation testbed with new software and hardware functionalities. It blends web service technology and operating system virtualization technologies with emerging Internet of Things technologies enabling CI for wireless networks. Moreover, we also extend an existing qualitative methodology for comparing similar frameworks and identify and discuss open challenges for wider use of CI practices in wireless technology development.
description: This work has been accepted for publication in IEEE Communications Magazine
Utilizing Neural Networks and Linguistic Metadata for Early Detection of Depression Indications in Text Sequences
Creators: name: Trotzek, Marcel
name: Koitka, Sven
name: Friedrich, Christoph M.
Publisher: name: arXiv
Year: 2018
Subjects: subject: Computation and Language (cs.CL)
subject: Information Retrieval (cs.IR)
subject: FOS: Computer and information sciences

description: Depression is ranked as the largest contributor to global disability and is also a major reason for suicide. Still, many individuals suffering from forms of depression are not treated for various reasons. Previous studies have shown that depression also has an effect on language usage and that many depressed individuals use social media platforms or the internet in general to get information or discuss their problems. This paper addresses the early detection of depression using machine learning models based on messages on a social platform. In particular, a convolutional neural network based on different word embeddings is evaluated and compared to a classification based on user-level linguistic metadata. An ensemble of both approaches is shown to achieve state-of-the-art results in a current early detection task. Furthermore, the currently popular ERDE score as metric for early detection systems is examined in detail and its drawbacks in the context of shared tasks are illustrated. A slightly modified metric is proposed and compared to the original score. Finally, a new word embedding was trained on a large corpus of the same domain as the described task and is evaluated as well.
description: This work has been submitted to the IEEE and has been accepted for future publication in IEEE Transactions on Knowledge and Data Engineering. 14 pages, 3 figures, 7 tables
Ethanol and Hydrogen gas-sensing properties of CuO-CuFe2O4 nanostructured thin films
Creators: name: De, Saptarshi
name: Venkataramani, N.
name: Prasad, Shiva
name: Dusane, R. O.
name: Presmanes, Lionel
name: Thimont, Y.
name: Tailhades, P.
name: Baco-Carles, Valerie
name: Bonningue, Corine
name: P, Sumangala T.
name: Barnabe, Antoine
Publisher: name: arXiv
Year: 2018
Subjects: subject: Applied Physics (physics.app-ph)
subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: Nanocrystalline CuO-CuFe2O4 composite thin films were developed from CuFeO2 ceramic target using a radio frequency sputtering method followed by a thermal oxidation process. This fabrication process helps to develop porous sensing layers which are highly desirable for solid state resistive gas sensors. Their sensing properties towards ethanol and hydrogen gas in dry air were examined at the operating temperatures ranging from 250 deg C to 500 deg C. The electrical transients during adsorption and desorption of the test gases were fitted with the Langmuir single site gas adsorption model. A composite thin film with a total thickness of 25 nm showed highest response (79%) towards hydrogen (500 ppm) at the operating temperature of 400 deg C. The shortest response time (tres) was found to be ~60 and ~90 seconds for hydrogen and ethanol respectively. The dependence of the response of the sensor on gas concentration (10-500 ppm) was also studied.
description: 7 pages, 6 figures, This paper has been submitted in a reputed journal on Jan 06, 2018, This work has been submitted to the IEEE for possible publication
title: Strobe statement for: "Health-related quality of life of adults with cutaneous leishmaniasis at ALERT Hospital, Addis Ababa, Ethiopia"
Creators: name: Lambert, Saba
Publisher: name: London School of Hygiene & Tropical Medicine
Year: 2024

description: A Strobe statement document made available to support the research article, "Health-related quality of life of adults with cutaneous leishmaniasis at ALERT Hospital, Addis Ababa, Ethiopia". This study aimed to assess the health-related quality of life (HRQoL) using the Amharic version of the Dermatology Life Quality Index (DLQI) in adults diagnosed with active Cutaneous leishmaniasis (CL).
Hybrid LISA for Wideband Multiuser Millimeter Wave Communication Systems under Beam Squint
Creators: name: González-Coma, José P.
name: Utschick, Wolfgang
name: Castedo, Luis
Publisher: name: arXiv
Year: 2018
Subjects: subject: Information Theory (cs.IT)
subject: FOS: Computer and information sciences

description: This work jointly addresses user scheduling and precoder/combiner design in the downlink of a wideband millimeter wave (mmWave) communications system. We consider Orthogonal Frequency Division Multiplexing (OFDM) modulation to overcome channel frequency selectivity and obtain a number of equivalent narrowband channels. Hence, the main challenge is that the analog preprocessing network is frequency flat and common to all the users at the transmitter side. Moreover, the effect of the signal bandwidth over the Uniform Linear Array (ULA) steering vectors has to be taken into account to design the hybrid precoders and combiners. The proposed algorithmic solution is based on Linear Successive Allocation (LISA), which greedily allocates streams to different users and computes the corresponding precoders and combiners. By taking into account the rank limitations imposed by the hardware at transmission and reception, the performance loss in terms of achievable sum rate for the hybrid approach is negligible. Numerical experiments show that the proposed method exhibits excellent performance with reasonable computational complexity.
description: This work has been submitted to the IEEE for possible publication
MOESM1 of Childhood malaria case incidence in Malawi between 2004 and 2017: spatio-temporal modelling of climate and non-climate factors
Creators: name: Chirombo, James
name: Ceccato, Pietro
name: Lowe, Rachel
name: Terlouw, Dianne
name: Thomson, Madeleine
name: Gumbo, Austin
name: Diggle, Peter
name: Read, Jonathan
Publisher: name: figshare
Year: 2020
Subjects: subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: FOS: Biological sciences
subject: Biological Sciences not elsewhere classified
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: Additional file 1. Exploratory analysis, model fit and diagnostics.
Additional file 1 of Patient and physician factors associated with Oncotype DX and adjuvant chemotherapy utilization for breast cancer patients in New Hampshire, 2010–2016
Creators: name: Schwedhelm, Thomas M.
name: Rees, Judy R.
name: Onega, Tracy
name: Zipkin, Ronnie J.
name: Schaefer, Andrew
name: Celaya, Maria O.
name: Moen, Erika L.
Publisher: name: figshare
Year: 2020
Subjects: Biotechnology
Cancer
Science Policy
Hematology

description: Additional file 1.
Student Conceptions of Assessment: Regulatory Responses to Our Practices
Creators: name: Brown, Gavin T. L.
Publisher: name: The University of Auckland
Year: 2022
Subjects: subject: 170103 Educational Psychology
subject: FOS: Psychology
subject: 130303 Education Assessment and Evaluation
subject: FOS: Educational sciences

description: Purpose: Universities assess and evaluate students concerning competence in essential disciplinary knowledge and skills. Those assessments impact learners’ attitudes, beliefs, and emotions. Negative impacts may be overcome if students regulate their responses to assessment and feedback. Design/Approach/Methods: This article systematically locates research studies that cite three key early papers around student conceptions of assessment (SCoA). A narrative synthesis is based on 22 papers. Findings: In addition to the SCoA, 11 different research inventories reveal a variety of regulatory responses that are enhanced when assessments are deliberately formative, fair, and trustworthy. There is broad interest in this phenomenon but little consistency in methods, and even the SCoA has little consistency in factor structure across jurisdictions. Only one study provided an objective behavioral measure to validate self-reports, which are the dominant form of research. Originality/Value: This review gives readers insights into how assessment influences student thinking and how student cognition can regulate success.
Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes
Creators: name: Tuyen, Le Pham
name: Vien, Ngo Anh
name: Layek, Abu
name: Chung, TaeChoong
Publisher: name: arXiv
Year: 2018
Subjects: subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: In recent years, reinforcement learning has achieved many remarkable successes due to the growing adoption of deep learning techniques and the rapid growth in computing power. Nevertheless, it is well-known that flat reinforcement learning algorithms are often not able to learn well and data-efficient in tasks having hierarchical structures, e.g. consisting of multiple subtasks. Hierarchical reinforcement learning is a principled approach that is able to tackle these challenging tasks. On the other hand, many real-world tasks usually have only partial observability in which state measurements are often imperfect and partially observable. The problems of RL in such settings can be formulated as a partially observable Markov decision process (POMDP). In this paper, we study hierarchical RL in POMDP in which the tasks have only partial observability and possess hierarchical properties. We propose a hierarchical deep reinforcement learning approach for learning in hierarchical POMDP. The deep hierarchical RL algorithm is proposed to apply to both MDP and POMDP learning. We evaluate the proposed algorithm on various challenging hierarchical POMDP.
description: This work has been submitted to the IEEE for possible publication
Circularly Pulse-Shaped Precoding for OFDM: A New Waveform and Its Optimization Design for 5G New Radio
Creators: name: Huang, Yenming
name: Su, Borching
Publisher: name: arXiv
Year: 2018
Subjects: subject: Information Theory (cs.IT)
subject: FOS: Computer and information sciences

description: A new circularly pulse-shaped (CPS) precoding orthogonal frequency division multiplexing (OFDM) waveform, or CPS-OFDM for short, is proposed in this paper. CPS-OFDM, characterized by user-specific precoder flexibility, possesses the advantages of both low out-of-subband emission (OSBE) and low peak-to-average power ratio (PAPR), which are two major desired physical layer signal properties for various scenarios in 5G New Radio (NR), including fragmented spectrum access, new types of user equipments (UEs), and communications at high carrier frequencies. As opposed to most of existing waveform candidates using windowing or filtering techniques, CPS-OFDM prevents block extension that causes extra inter-block interference (IBI) and envelope fluctuation unfriendly to signal reception and power amplifier (PA) efficiency, respectively. An optimization problem of the prototype shaping vector built in the CPS precoder is formulated to minimize the variance of instantaneous power (VIP) with controllable OSBE power (OSBEP) and noise enhancement penalty (NEP). In order to solve the optimization problem involving a quartic objective function, the majorization-minimization (MM) algorithmic framework is exploited. By proving the convexity of the proposed problem, the globally optimal solution invariant of coming data is guaranteed to be attained via numbers of iterations. Simulation results demonstrate the advantages of the proposed scheme in terms of detection reliability and spectral efficiency for practical 5G cases such as asynchronous transmissions and mixed numerologies.
description: 15 pages, 21 figures. This work has been submitted to the IEEE for possible publication
Additional file 1 of De novo transcriptome assembly and population genetic analyses of an important coastal shrub, Apocynum venetum L
Creators: name: Yuan, Na
name: Li, Mimi
name: Chunlin Jia
Publisher: name: figshare
Year: 2020
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 1: Fig. S1. Length distribution of assembled unigenes (A) and the number of reads mapped to each unigene (B) that generated from A. venetum transcriptome.
Additional file 4 of De novo transcriptome assembly and population genetic analyses of an important coastal shrub, Apocynum venetum L
Creators: name: Yuan, Na
name: Li, Mimi
name: Chunlin Jia
Publisher: name: figshare
Year: 2020
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 4: Fig. S3. Correlation between genetic differentiation and log geographical distance for the A. venetum populations in Jiangsu Province.
Covert Transmission with a Self-sustained Relay
Creators: name: Hu, Jinsong
name: Yan, Shihao
name: Shu, Feng
name: Wang, Jiangzhou
Publisher: name: arXiv
Year: 2018
Subjects: subject: Information Theory (cs.IT)
subject: FOS: Computer and information sciences

description: This work examines the possibility, performance limits, and associated costs for a self-sustained relay to transmit its own covert information to a destination on top of forwarding the source's information. Since the source provides energy to the relay for forwarding its information, the source does not allow the relay's covert transmission and is to detect it. Considering the time switching (TS) and power splitting (PS) schemes for energy harvesting, where all the harvested energy is used for transmission at the self-sustained relay, we derive the minimum detection error probability $ξ^{\ast}$ at the source, based on which we determine the maximum effective covert rate $Ψ^{\ast}$ subject to a given covertness constraint on $ξ^{\ast}$. Our analysis shows that $ξ^{\ast}$ is the same for the TS and PS schemes, which leads to the fact that the cost of achieving $Ψ^{\ast}$ in both the two schemes in terms of the required increase in the energy conversion efficiency at the relay is the same, although the values of $Ψ^{\ast}$ in these two schemes can be different in specific scenarios. For example, the TS scheme outperforms the PS scheme in terms of achieving a higher $Ψ^{\ast}$ when the transmit power at the source is relatively low. If the covertness constraint is tighter than a specific value, it is the covertness constraint that limits $Ψ^{\ast}$, and otherwise it is upper bound on the energy conversion efficiency that limits $Ψ^{\ast}$.
description: This work has been submitted to the IEEE for possible publication
Fairness and Sum-Rate Maximization via Joint Channel and Power Allocation in Uplink SCMA Networks
Creators: name: Evangelista, Joao V. C.
name: Sattar, Zeeshan
name: Kaddoum, Georges
name: Chaaban, Anas
Publisher: name: arXiv
Year: 2018
Subjects: subject: Information Theory (cs.IT)
subject: FOS: Computer and information sciences

description: In this work, we consider a sparse code multiple access uplink system, where $J$ users simultaneously transmit data over $K$ subcarriers, such that $J > K$, with a constraint on the power transmitted by each user. To jointly optimize the subcarrier assignment and the transmitted power per subcarrier, two new iterative algorithms are proposed, the first one aims to maximize the sum-rate (Max-SR) of the network, while the second aims to maximize the fairness (Max-Min). In both cases, the optimization problem is of the mixed-integer nonlinear programming (MINLP) type, with non-convex objective functions, which are generally not tractable. We prove that both joint allocation problems are NP-hard. To address these issues, we employ a variant of the block successive upper-bound minimization (BSUM) \cite{razaviyayn.2013} framework, obtaining polynomial-time approximation algorithms to the original problem. Moreover, we evaluate the algorithms' robustness against outdated channel state information (CSI), present an analysis of the convergence of the algorithms, and a comparison of the sum-rate and Jain's fairness index of the novel algorithms with three other algorithms proposed in the literature. The Max-SR algorithm outperforms the others in the sum-rate sense, while the Max-Min outperforms them in the fairness sense.
description: This work has been submitted to the IEEE for possible publication
Optimal Sensor Data Fusion Architecture for Object Detection in Adverse Weather Conditions
Creators: name: Pfeuffer, Andreas
name: Dietmayer, Klaus
Publisher: name: arXiv
Year: 2018
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: A good and robust sensor data fusion in diverse weather conditions is a quite challenging task. There are several fusion architectures in the literature, e.g. the sensor data can be fused right at the beginning (Early Fusion), or they can be first processed separately and then concatenated later (Late Fusion). In this work, different fusion architectures are compared and evaluated by means of object detection tasks, in which the goal is to recognize and localize predefined objects in a stream of data. Usually, state-of-the-art object detectors based on neural networks are highly optimized for good weather conditions, since the well-known benchmarks only consist of sensor data recorded in optimal weather conditions. Therefore, the performance of these approaches decreases enormously or even fails in adverse weather conditions. In this work, different sensor fusion architectures are compared for good and adverse weather conditions for finding the optimal fusion architecture for diverse weather situations. A new training strategy is also introduced such that the performance of the object detector is greatly enhanced in adverse weather scenarios or if a sensor fails. Furthermore, the paper responds to the question if the detection accuracy can be increased further by providing the neural network with a-priori knowledge such as the spatial calibration of the sensors.
description: This work has been submitted to the IEEE for possible publication
Efficient deep blue (CIE ∼0.08) fluorophore-based benzimidazole with hybridized local and charge transfer (HLCT) excited state for OLEDs
Creators: name: Girase, Jaipal Devesing
name: Tagare, Jairam
name: Mukherjee, Susmita
name: Chakrabrati, Tanwistha
name: Perumal, Ajay
name: Vaidyanathan, Sivakumar
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: Biophysics
subject: 29999 Physical Sciences not elsewhere classified
subject: FOS: Physical sciences
subject: Physiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: 69999 Biological Sciences not elsewhere classified

description: Development of efficient deep blue fluorophore with Commission Internationale de l’Eclairage (CIE)y value <0.1 is of great importance for display technology. Herein, we designed and synthesized a thermally stable deep blue emissive material 3-(2-(4′′-(1-phenyl-1H-benzo[d]imidazol-2-yl)-[1,1′:4′,1″-terphenyl]-4-yl)-1H-phenanthro[9,10-d]imidazol-1-yl)benzonitrile (MCNPIBI) by integrating moderate donor and acceptor, namely, phenanthroimidazole (PI) and benzimidazole with cyanophenyl (-CN) group at N1 position of the PI to tune the CT component in the excited states. The systematic theoretical and photophysical study reveals the MCNPIBI with hybridized local and charge transfer (HLCT) excited states. Time-dependent density functional theory (TD-DFT) calculation suggests that the reverse intersystem crossing (RISC) process in MCNPIBI occurs from high-lying triplet states to a singlet state. Furthermore, the synthesized deep blue emissive materials were employed as dopants in multilayer organic light emitting diode (OLED) devices, thus resulting in deep-blue electroluminescence (EL) with an emission wavelength of 447 nm and CIE coordinates of (0.15, 0.08), which are close to the standard values for blue emitters, as suggested by NTSC (0.14, 0.08). The OLED device displays a maximum current efficiency of 2.78 cd A−1, a maximum power efficiency of 1.94 lm W−1, and a maximum external quantum efficiency of 3.69%, respectively. In addition, the OLED device has a low turn in voltage of 3.8 V.
Faster Bounding Box Annotation for Object Detection in Indoor Scenes
Creators: name: Adhikari, Bishwo
name: Peltomäki, Jukka
name: Puura, Jussi
name: Huttunen, Heikki
Publisher: name: arXiv
Year: 2018
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences

description: This paper proposes an approach for rapid bounding box annotation for object detection datasets. The procedure consists of two stages: The first step is to annotate a part of the dataset manually, and the second step proposes annotations for the remaining samples using a model trained with the first stage annotations. We experimentally study which first/second stage split minimizes to total workload. In addition, we introduce a new fully labeled object detection dataset collected from indoor scenes. Compared to other indoor datasets, our collection has more class categories, different backgrounds, lighting conditions, occlusion and high intra-class differences. We train deep learning based object detectors with a number of state-of-the-art models and compare them in terms of speed and accuracy. The fully annotated dataset is released freely available for the research community.
description: This work has been submitted to the IEEE for possible publication
title: 01_0663
Creators: name: Wesley Baldwin, John
name: Baldwin, John W.
Publisher: name: NAKALA - https://nakala.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2018
Subjects: subject: LaMOP
subject: Laboratoire de Médiévistique Occidentale de Paris

description: L'ensemble de ces notes ont été crée par John Baldwin lors d'une de ses premières périodes de résidence à Paris. Ces documents comprennent tous les magistri qu’il avait pu rencontrer dans ses sources. Aux XIIème et XIIIème siècles, les universités n'existant pas encore, le titre de magister s'il évoque certainement une compétence n'est pas rattaché de façon systématique au passage par les écoles. De surcroît, les magistris sont le plus souvent désignés par leur seul prénom. La lecture de ces données est donc difficile et suppose un long travail pour tenter d'identifier un individu auquel on pourrait rattacher plusieurs mentions. John Baldwin avait donc renoncé à utiliser ces données pour donner un prolongement à sa magnifique étude sur les gradués d'université et leur emploi par les Capétiens et les Plantagenêts. Néanmoins, il a conservé ces données et elles sont potentiellement très utile dans le cadre de Studium, comme le sont toutes les mentions dans les volumes des Fasti Ecclesiae Gallicanae de chanoines portant ce titre de magister sans autres précisions. L'ampleur des dépouillements rend ces données très utiles et nous devons une grande reconnaissance à John Baldwin pour avoir pris la peine de faire photocopier ses fiches et de nous les avoir transmises amicalement.
Les données ainsi que les images des fiches sont accessibles sur le site Internet à l'adresse suivante : http://studium-baldwin.lamop.fr/.
Les transcriptions des fiches ont été effectuées par des étudiants de Paris 1 Panthéon - Sorbonne mais elles n'ont pas été corrigées par la suite.
description: Relation: https://lamop.hypotheses.org/
Additional file 2 of De novo transcriptome assembly and population genetic analyses of an important coastal shrub, Apocynum venetum L
Creators: name: Yuan, Na
name: Li, Mimi
name: Chunlin Jia
Publisher: name: figshare
Year: 2020
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 2: Fig. S2. KOG classification of assembled unigenes of A. venetum.
A Tensor Factorization Method for 3D Super-Resolution with Application to Dental CT
Creators: name: Hatvani, Janka
name: Basarab, Adrian
name: Tourneret, Jean-Yves
name: Gyöngy, Miklós
name: Kouamé, Denis
Publisher: name: arXiv
Year: 2018
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: Available super-resolution techniques for 3D images are either computationally inefficient prior-knowledge-based iterative techniques or deep learning methods which require a large database of known low- and high-resolution image pairs. A recently introduced tensor-factorization-based approach offers a fast solution without the use of known image pairs or strict prior assumptions. In this article this factorization framework is investigated for single image resolution enhancement with an off-line estimate of the system point spread function. The technique is applied to 3D cone beam computed tomography for dental image resolution enhancement. To demonstrate the efficiency of our method, it is compared to a recent state-of-the-art iterative technique using low-rank and total variation regularizations. In contrast to this comparative technique, the proposed reconstruction technique gives a 2-order-of-magnitude improvement in running time -- 2 minutes compared to 2 hours for a dental volume of 282$\times$266$\times$392 voxels. Furthermore, it also offers slightly improved quantitative results (peak signal-to-noise ratio, segmentation quality). Another advantage of the presented technique is the low number of hyperparameters. As demonstrated in this paper, the framework is not sensitive to small changes of its parameters, proposing an ease of use.
description: This work has been submitted to the IEEE for possible publication
Classification of Building Information Model (BIM) Structures with Deep Learning
Creators: name: Lomio, Francesco
name: Farinha, Ricardo
name: Laasonen, Mauri
name: Huttunen, Heikki
Publisher: name: arXiv
Year: 2018
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences

description: In this work we study an application of machine learning to the construction industry and we use classical and modern machine learning methods to categorize images of building designs into three classes: Apartment building, Industrial building or Other. No real images are used, but only images extracted from Building Information Model (BIM) software, as these are used by the construction industry to store building designs. For this task, we compared four different methods: the first is based on classical machine learning, where Histogram of Oriented Gradients (HOG) was used for feature extraction and a Support Vector Machine (SVM) for classification; the other three methods are based on deep learning, covering common pre-trained networks as well as ones designed from scratch. To validate the accuracy of the models, a database of 240 images was used. The accuracy achieved is 57% for the HOG + SVM model, and above 89% for the neural networks.
description: This work has been submitted to the IEEE for possible publication
Additional file 3 of De novo transcriptome assembly and population genetic analyses of an important coastal shrub, Apocynum venetum L
Creators: name: Yuan, Na
name: Li, Mimi
name: Chunlin Jia
Publisher: name: figshare
Year: 2020
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 3: Table S1. Migrate-n results of historical gene flow and BayesAss results of contemporary gene flow with 95% confidence among the Apocynum venetum populations.
title: Разработка модуля программного обеспечения переводчика слов жестового языка в звуковой формат
title: Developing a Software Module for Translating Words from Sign Language into an Audio Format
Creators: name: Семенова, Валерия Олеговна
name: Семенова, Лариса Леонидовна
Publisher: name: Издательский центр СурГУ
Year: 2022

description: В статье определены и сформулированы основные требования к нейронной сети с функциями распознавания жестов кистей рук, проведено исследование существующих подходов на соответствие этим требованиям. Составлен перечень для имитации реальных условий использования модуля распознавания жестов «Диалогового сурдопереводчика», дополнительно проведены измерения необходимых характеристик камеры для корректной работы нейронной сети с целью получения качества распознавания кисти руки в режиме реального времени не ниже 75 %. Разработан прототип нейронной сети, представлен успешный результат различения левой и правой руки в имитационных условиях. В качестве перспективы заявлена необходимость обеспечения работы программного обеспечения не только с жестами, но и с речью для дальнейшего развития технологий инклюзии людей с коммуникативными трудностями.
description: The article determines and formulates the main requirements to a neural network that detects hand gestures. A study of existing approaches is conducted on the matter of their compliance with the requirements. A list of real conditions is compiled to imitate an application of a sign recognition module “Dialogue Sign Language Translator”. In addition to that, the required camera characteristics were measured for proper operation of the neural network in order to obtain a real-time palm recognition quality of at least 75 %. A prototype of a neural network was developed. The study shows the efficiency at differentiating left and right hands during imitation. From the prospect point of view, it is necessary to build the software oper-ating both with signs and with speech in order to continue developing the technologies for inclusion of people with communication difficulties.
On Passivity, Reinforcement Learning and Higher-Order Learning in Multi-Agent Finite Games
Creators: name: Gao, Bolin
name: Pavel, Lacra
Publisher: name: arXiv
Year: 2018
Subjects: subject: Optimization and Control (math.OC)
subject: Computer Science and Game Theory (cs.GT)
subject: Systems and Control (eess.SY)
subject: FOS: Mathematics
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: In this paper, we propose a passivity-based methodology for analysis and design of reinforcement learning in multi-agent finite games. Starting from a known exponentially-discounted reinforcement learning scheme, we show that convergence to a Nash distribution can be shown in the class of games characterized by the monotonicity property of their (negative) payoff. We further exploit passivity to propose a class of higher-order schemes that preserve convergence properties, can improve the speed of convergence and can even converge in cases whereby their first-order counterpart fail to converge. We demonstrate these properties through numerical simulations for several representative games.
description: 14 pages, 19 figures. This work has been submitted to the IEEE for possible publication
Distributed GNE seeking under partial-decision information over networks via a doubly-augmented operator splitting approach
Creators: name: Pavel, Lacra
Publisher: name: arXiv
Year: 2018
Subjects: subject: Optimization and Control (math.OC)
subject: Computer Science and Game Theory (cs.GT)
subject: Systems and Control (eess.SY)
subject: FOS: Mathematics
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: We consider distributed computation of generalized Nash equilibrium (GNE) over networks, in games with shared coupling constraints. Existing methods require that each player has full access to opponents' decisions. In this paper, we assume that players have only partial-decision information, and can communicate with their neighbours over an arbitrary undirected graph. We recast the problem as that of finding a zero of a sum of monotone operators through primal-dual analysis. To distribute the problem, we doubly augment variables, so that each player has local decision estimates and local copies of Lagrangian multipliers. We introduce a single-layer algorithm, fully distributed with respect to both primal and dual variables. We show its convergence to a variational GNE with fixed step-sizes, by reformulating it as a forward-backward iteration for a pair of doubly-augmented monotone operators.
description: 12 pages, 5 figures. This work has been submitted to the IEEE for possible publication
MOESM1 of Cytological observation of anther structure and genetic investigation of a thermo-sensitive genic male sterile line 373S in Brassica napus L
Creators: name: Sun, Yanyan
name: Zhang, Dongsuo
name: Wang, Zhenzhen
name: Guo, Yuan
name: Sun, Xiaomin
name: Li, Wei
name: Zhi, Wenliang
name: Hu, Shengwu
Publisher: name: figshare
Year: 2020
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Plant Biology
subject: Computational Biology

description: Additional file 1: Table S1. Pearson correlation coefficient between average of 3-day highest, lowest and mean temperature and male fertility index of 373S by pot cultivation (E1, flower period 11/3/2017â€“30/3/2017, Yangling, Shaanxi).
title: Моделирование и реализация командной проектной деятельности в соответствии со стандартами CDIO
title: Simulating and Implementing a Team Project Activity according to the CDIO Standards
Creators: name: Тараканов, Дмитрий Викторович
name: Запевалова, Лариса Юрьевна
Publisher: name: Издательский центр СурГУ
Year: 2022

description: Представлен способ моделирования и реализации командной работы при проектировании системы автоматизированного управления комплексом «Локальная ферма». Для формирования проектных команд, оценки своевременного и качественного выполнения работы использована Е-сетевая логико-динамическая модель. Продемонстрирована успешность применения междисциплинарного подхода, приемов декомпозиции проекта на этапы и делегирования заданий участникам команд, адаптации проектных решений при создании пилотной версии оригинальной автоматизированной системы управления комплексом «Локальная ферма».
description: The article proposes a method for simulating and implementing a team activity when designing an automated control system for the “Local farm” complex. E-network logical and dynamic model was used to group project teams and to assess in-time and high-quality work performance. The success of the interdisciplinary approach, methods of decomposition of the project into steps and delegation of the tasks to the teams’ participants is shown. The efficiency of adaptation of project decisions when creating a pilot version of an automated control system for the “Local farm” complex is presented.
Syntheses, structures and antimicrobial properties of complexes based on 2-hydroxybenzaldehyde-4-aminoantipyrine Schiff base
Creators: name: Tang, Quan
name: Hu, Jing
name: Ding, Yi-Jie
name: Zhang, Yi-Fan
name: Li, Hui-Fang
name: Xu, Ming
name: Yang, Xin-Cheng
name: Liang, Lili
name: Li, Wen-Ge
Publisher: name: Taylor & Francis
Year: 2021
Subjects: subject: Biophysics
subject: Biochemistry
subject: Molecular Biology
subject: Environmental Sciences not elsewhere classified
subject: Chemical Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Plant Biology
subject: FOS: Biological sciences

description: Two monomeric complexes, [NiL2·3H2O] (1) and [Nd2L3(NO3)3] (2), with a tridentate ONO-donor Schiff base ligand HL (HL = 2-hydroxybenzaldehyde-4-aminoantipyrine) have been synthesized. Single-crystal X-ray diffraction analysis indicates that the asymmetric unit of 1 contains one Ni(II) and two L− ligands, while 2 consists of two Nd(III) ions, three L− ligands, and three NO3− ions. Complexes 1 and 2 are both 0-D discrete monomers, and there are intermolecular π–π interactions in 1 and intramolecular π–π interactions in 2. The discrete [NiL2·3H2O] monomers are further connected through π–π interactions, resulting in a 3-D supramolecular structure. Powder XRD and TG-DSC were performed for 1 and 2. Antimicrobial experiments show that 1 displays significant antibacterial effect against Bacillary dysentery and Escherichia coli in comparison with that of Schiff base ligand.
Underlay Drone Cell for Temporary Events: Impact of Drone Height and Aerial Channel Environments
Creators: name: Zhou, Xiaohui
name: Durrani, Salman
name: Guo, Jing
name: Yanikomeroglu, Halim
Publisher: name: arXiv
Year: 2018
Subjects: subject: Information Theory (cs.IT)
subject: FOS: Computer and information sciences

description: Providing seamless connection to a large number of devices is one of the biggest challenges for the Internet of Things (IoT) networks. Using a drone as an aerial base station (ABS) to provide coverage to devices or users on ground is envisaged as a promising solution for IoT networks. In this paper, we consider a communication network with an underlay ABS to provide coverage for a temporary event, such as a sporting event or a concert in a stadium. Using stochastic geometry, we propose a general analytical framework to compute the uplink and downlink coverage probabilities for both the aerial and the terrestrial cellular system. Our framework is valid for any aerial channel model for which the probabilistic functions of line-of-sight (LOS) and non-line-of-sight (NLOS) links are specified. The accuracy of the analytical results is verified by Monte Carlo simulations considering two commonly adopted aerial channel models. Our results show the non-trivial impact of the different aerial channel environments (i.e., suburban, urban, dense urban and high-rise urban) on the uplink and downlink coverage probabilities and provide design guidelines for best ABS deployment height.
description: This work is accepted to appear in IEEE Internet of Things Journal Special Issue on UAV over IoT. arXiv admin note: text overlap with arXiv:1801.05948
MOESM2 of Cytological observation of anther structure and genetic investigation of a thermo-sensitive genic male sterile line 373S in Brassica napus L
Creators: name: Sun, Yanyan
name: Zhang, Dongsuo
name: Wang, Zhenzhen
name: Guo, Yuan
name: Sun, Xiaomin
name: Li, Wei
name: Zhi, Wenliang
name: Hu, Shengwu
Publisher: name: figshare
Year: 2020
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Plant Biology
subject: Computational Biology

description: Additional file 2: Table S2. Pearson correlation coefficient between average of 3-day highest, lowest and mean temperature and male fertility index in the field in 2016 (E2, flower period 30/3/2016â€“15/4/2016, Yangling, Shaanxi).
Leakage Mitigation in Heterodyne FMCW Radar For Small Drone Detection with Stationary Point Concentration Technique
Creators: name: Park, Junhyeong
name: Park, Seungwoon
name: Kim, Do-Hoon
name: Park, Seong-Ook
Publisher: name: arXiv
Year: 2018
Subjects: subject: Signal Processing (eess.SP)
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Recently, as the drones have become smaller and smarter, they are emerging as new threats to the military and the public. To prevent the threats, the development of the radar to detect the small drones is needed. The frequency modulated continuous wave (FMCW) radar is one of the radar types for the drone detection. The heterodyne architecture for the FMCW radar is often applied to resolve the dc offset problem. However, the leakage from a transmitter into a receiver, the notorious problem of the FMCW radar, is still a challenging problem. Especially, the phase noise of the leakage increases the noise floor and deteriorates the signal to noise ratio. In order to mitigate this problem, in this paper, the stationary point concentration technique is proposed. Without additional hardware, the proposed technique can be implemented through frequency planning and digital signal processing. The results show that the proposed technique significantly lowers the noise floor over the desired range domain.
description: This work has been submitted to the IEEE for possible publication. arXiv admin note: text overlap with arXiv:1807.06324
Cluster categories and rational curves
Creators: name: Hua, Zheng
name: Keller, Bernhard
Publisher: name: arXiv
Year: 2018
Subjects: subject: Algebraic Geometry (math.AG)
subject: Category Theory (math.CT)
subject: Representation Theory (math.RT)
subject: FOS: Mathematics
subject: 14Exx, 14B12, 14A22, 13F60

description: We study rational curves on smooth complex Calabi--Yau threefolds via noncommutative algebra. By the general theory of derived noncommutative deformations due to Efimov, Lunts and Orlov, the structure sheaf of a rational curve in a smooth CY 3-fold $Y$ is pro-represented by a nonpositively graded dg algebra $Γ$. The curve is called nc rigid if $H^0Γ$ is finite dimensional. When $C$ is contractible, $H^0Γ$ is isomorphic to the contraction algebra defined by Donovan and Wemyss. More generally, one can show that there exists a $Γ$ pro-representing the (derived) multi-pointed deformation (defined by Kawamata) of a collection of rational curves $C_1,\ldots,C_t$ so that ${\mathrm{dim}}({\rm{Hom}}_Y({\mathcal{O}}_{C_i},{\mathcal{O}}_{C_j}))=δ_{ij}$. The collection is called nc rigid if $H^0Γ$ is finite dimensional. We prove that $Γ$ is a homologically smooth bimodule 3CY algebra. As a consequence, we define a (2CY) cluster category ${\mathcal{C}}_Γ$ for such a collection of rational curves in $Y$. It has finite-dimensional morphism spaces iff the collection is nc rigid. When $\bigcup_{i=1}^tC_i$ is (formally) contractible by a morphism $\hat{Y}\to \hat{X}$, ${\mathcal{C}}_Γ$ is equivalent to the singularity category of $\hat{X}$ and thus categorifies the contraction algebra of Donovan and Wemyss. The Calabi-Yau structure on $Y$ determines a canonical class $[w]$ (defined up to right equivalence) in the zeroth Hochschild homology of $H^0Γ$. Using our previous work on the noncommutative Mather--Yau theorem and singular Hochschild cohomology, we prove that the singularities underlying a 3-dimensional smooth flopping contraction are classified by the derived equivalence class of the pair $(H^0Γ, [w])$. We also give a new necessary condition for contractibility of rational curves in terms of $Γ$.
description: This is a final version where several errors have been corrected. To appear in Geometry and Topology
title: Сравнение методов классификации русскоязычных новостных текстов с использованием алгоритмов машинного обучения
title: Comparing Classification Methods for News Texts in Russian Using Machine Learning Algorithms
Creators: name: Челышев, Эдуард Артурович
name: Оцоков, Шамиль Алиевич
name: Раскатова, Марина Викторовна
name: Щёголев, Павел
Publisher: name: Издательский центр СурГУ
Year: 2022

description: В работе рассмотрена задача классификации русскоязычных новостных текстов с использованием таких алгоритмов машинного обучения, как наивный байесовский классификатор, случайный лес деревьев решений, логистическая регрессия и искусственная нейронная сеть. Для решения задачи использовались тексты новостного интернет-портала Lenta.ru, относящиеся к девяти различным классам – рубрикам новостных статей. Программная реализация в рамках данной работы проводилась с использованием языка программирования Python. Проведена предварительная обработка текстовых данных: удаление нерелевантных символов и приведение их к общему регистру, токенизация, нормализация, удаление стоп-слов и векторизация текстов. Для реализации искусственной нейронной сети в рамках данной работы использовались библиотеки Tensorflow и Keras языка программирования Python. Для каждой из использованных моделей машинного обучения были определены значения гиперпараметров, дающих наивысшее качество классификации, с использованием ряда метрик: precision, recall и F-мера. Проведен сравнительный анализ использованных алгоритмов. Указаны возможные пути дальнейшей работы в рамках рассматриваемой задачи.
description: The article discusses the problem of classification of news texts in Russian using such machine learning algorithms as naive Bayes classifier, random decision forests, logistic regression, and artificial neural network. The texts of the Internet news portal Lenta.ru were selected from nine different classes – sections of news articles to solve the problem. The software implementation in the framework of the study was carried out using the Python programming language. The preprocessing of text data included removal of irrelevant characters and their reduction to a common register, tokenization, normalization, removal of stop words and vectorization of texts. Tensorflow and Keras libraries of the Python programming language were used to implement an artificial neural network. For each of the machine learning models used, hyperparameters values were determined in order to achieve the highest classification quality using a number of metrics: precision, recall and F-measure. A comparative analysis of the algorithms used was carried out. Possible ways for further study within the problem in question are specified.