Reviewerly/exHarmony huggingface dataset:
Embedding of FRPN in CNN architecture.

This paper extends the fully recursive perceptron network (FRPN) model for vectorial inputs to include deep convolutional neural networks (CNNs) which can accept multi-dimensional inputs. A FRPN consists of a recursive layer, which, given a fixed input, iteratively computes an equilibrium state. The unfolding realized with this kind of iterative mechanism allows to simulate a deep neural network with any number of layers. The extension of the FRPN to CNN results in an architecture, which we call convolutional-FRPN (C-FRPN), where the convolutional layers are recursive. The method is evaluated on several image classification benchmarks. It is shown that the C-FRPN consistently outperforms standard CNNs having the same number of parameters. The gap in performance is particularly large for small networks, showing that the C-FRPN is a very powerful architecture, since it allows to obtain equivalent performance with fewer parameters when compared with deep CNNs.
SR-Affine: High-quality 3D hand model reconstruction from UV Maps.

Under various poses and heavy occlusions,3D hand model reconstruction based on a single monocular RGB image has been a challenging problem in computer vision field for many years. In this paper, we propose a SR-Affine approach for high-quality 3D hand model reconstruction. First, we propose an encoder-decoder network architecture (AffineNet) for MANO hand reconstruction. Since MANO hand is not detailed, we further propose SRNet to up-sampling point-clouds by image super-resolution on the UV map. Many experiments demonstrate that our approach is robust and outperforms the state-of-the-art methods on standard benchmarks, including the FreiHAND and HO3D datasets.
Analisis Kepuasan Konsumen Terhadap Pelayanan Bengkel Menggunakan Metode Algoritma C4.5

Consumer satisfaction is one thing that is very important is assessing the level of service provided by the workshop to its consumers. The purpose of this study was to determine the quality of serviceto consumer satisfaction Zul Keluarga jaya workshop Pematangsiantar in terms of reliability, Responsiveness, Assurance, Emphaty, Tangibles to consumers Zul Keluarga Jaya workshop Pematangsiantar. In the Zul keluarga Jaya workshop Pematangsiantar the five aspects have not been measured with certainty, so the Zul Keluarga Jaya workshop Pematangsiantar found it difficult to determine which aspects should be improved. By using the C4.5 algorithm, the authors try to measure these five aspects so that a decision tree is formed. After doing a manual calculation, then the proof is done using Rapidminer software. Testing conducted with RapidMiner software using the apply model % performance. From the results of calculation using the C4.5 algorithm produced twelve (12) rule rules of the target to be achieved namely six (6) satisfied decisions and six (6) dissatisfied decisions, and the results of lesting with RapidMiner software resulted in an inspiration rate of 94,00%.
Knowledge Graph Oriented Anti-ship Combat Command Information Ontology Model

Aiming at the lack of standard knowledge representation framework in the construction of anti-ship combat knowledge graph, this paper proposes a knowledge representation model for anti-ship combat command based on ontology. The model extracts the high-dimensional concept space of operational command domain knowledge from the process of command information generation, and uses through logical modeling, then classifies concept categories and levels according to meta characteristics and abstract degree, so as to reduce the dimension of concept space. On this basis, ontology semantic model is constructed to extract and describe entities, attributes, relationships and other knowledge units in command information. It is proved that the model can extract and describe the domain knowledge of command information completely, and it is scientific and adaptive as the knowledge representation framework of anti-ship combat knowledge graph.
From Universal Classification to a Postcoordinated Universe

This chapter starts off from standard takes on knowledge organization and classification in libraries and encyclopedias, but then zeros in on the field of information retrieval, which develops in fundamental opposition to even the most visionary of library techniques. Coordinate indexing, the first technique in this lineage, is explicitly designed to eliminate the influence of librarians and other knowledge mediators by shifting expressive power from the classification system to the query and, by extension, to the information seeker. Order is no longer understood as a stable map to the universe of knowledge but increasingly as the outcome of a dynamic and purpose-driven process of ordering. The chapter closes by discussing coordinate indexing as a precursor of the relational model for database management.
Annual, seasonal and monthly projected changes in meteorological parameters under rcp based emission scenarios at Ludhiana (Punjab)

A study was conducted using CSIRO-Mk3-6-0 model to analyze the changes in meteorological parameters under four RCP scenarios during the 21st century at Ludhiana. The maximum temperature is predicted to increase from baseline (1970–2015) by 0.5 -1.0oC during mid-century (2020–2049) and by 1.2 - 2.4oC during end century (2066–2095) and the minimum temperature by 1.8 - 2.4oC during mid-century and by 2.0 - 5.3oC during end century. Projected annual rainfall decreased and its coefficient of variation (CV) increased (>300%) indicating increased erraticity. Solar radiation is predicted to decrease by nearly 4–6%. The CVs for temperature and radiation during winter season are high Indicating increased cloudiness with frequent heat/cold wave spells. Though cold wave spell may be favourable but the cloudy weather is not conducive for wheat. The monsoon season rainfall is projected to decrease during June, August and September. The rainfall for October is projected to increase which may hamper harvesting of kharif season crops.
Implementation of MOSSE Object Tracking Algorithm on FPGA with High Level Synthesis Approach

Video object tracking is significant topic of image processing aplications. A video tracking algorithm is should to track object in condition, variable light intensity, object occlusion , variable object size and variable object orientation. Considering these requirements, hardware with high processing capacity is needed. Hardware with high processing capacity creates disadvantages in applications such as mobile robot, flying vehicle, due to power consumption and hardware size. FPGA provides high performance in image processing applications by parallelism, processing big data capability and flexibility depending on design. In this paper, hardware architecture of Correlation filter based MOSSE video object tracking algorithm is desinged and designed algorithm is implemented on FPGA with high level synthesis aproach. Implementation of proposed hardware architecture on a single FPGA chip will create advantageous in applications where the payload is limited, such as mobile robots and unmanned aerial vehicles.
Research on forming of reading skills of primary school age children with special educational needs by modern typography

The paper presents the results of the study on reading skills of children of primary school age with special educational needs. Texts adapted by different print typefaces for primary school textbooks and modern typefaces used for children with dyslexia have been proposed as stimulating material. The quality and speed tasks' execution of printed in different fonts was evaluated. The results of the research indicate that the Inclusion UKR font has a positive impact on the reading skills forming of children with special educational needs. Further prospects for the study are to determine the effectiveness of using the Inclusion UKR font to optimize reading skills of children with special educational needs.
Learning Under High Cognitive Workload

This research investigates the impact of time pressure and individual differences on learning in a Real-Time Dynamic Decision Making (RTDDM) task. Our empirical results indicate that high time pressure generates high cognitive loads inhibiting learning. The results also show that high time pressure have a differential impact on the learning of individuals with high or low Working Memory (WM) capacity. We present a cognitive model based on ACT-R intended to explain learning in this task. Our cognitive model simulates learning by recognizing regularities in the decision task, and building “chunks” that guide decision making (instance-based learning). We describe how the model will be used to explain the impact of time pressure and WM capacity by varying the number of chunks acquired by the system given alternative time pressure conditions and individual differences.
siaNMS: Non-Maximum Suppression with Siamese Networks for Multi-Camera 3D Object Detection.

The rapid development of embedded hardware in autonomous vehicles broadens their computational capabilities, thus bringing the possibility to mount more complete sensor setups able to handle driving scenarios of higher complexity. As a result, new challenges such as multiple detections of the same object have to be addressed. In this work, a siamese network is integrated into the pipeline of a well-known 3D object detector approach to suppress duplicate proposals coming from different cameras via re-identification. Additionally, associations are exploited to enhance the 3D box regression of the object by aggregating their corresponding LiDAR frustums. The experimental evaluation on the nuScenes dataset shows that the proposed method outperforms traditional NMS approaches.
Employee Engagement At Green Park Hotels And Resorts Ltd. - A Case Study

Employee participation (Engagement) for any enterprise in the globalised era is a burning issue. Engaged workers are more likely to contribute to organisations' productivity. It also helps keep your commitment higher. Employee involvement means employees' level of commitment and commitment to their organisation and values. Corporate success depends on an employee's productivity, accelerated in the employee's commitment to his organisation. This article analyses the relevance and success of the employees involved in the development and growth of the company. This paper attempts to examine the various variables of employee participation. It can be used to provide an overview and references of some conceptual and practical work in the field of employee engagement in the hotel industry in India. The factors contributing to their overall impact on the organisation are measured by the data collected by means of a questionnaire in this study in the hotel industry. The study's main goal was to analyse and interpret the impact of employee commitment on the company's success through a structured questionnaire.
MuRF-Net: Multi-Receptive Field Pillars for 3D Object Detection from Point Cloud.

In this paper, we propose a point cloud based 3D object detection framework that accounts for both contextual and local information by leveraging multi-receptive field pillars, named as MuRF-Net. Recently, common pipelines can be divided into a voxel-based feature encoder and an object detector. During the feature encoding steps, contextual information is neglected, which is critical for the 3D object detection task. Thus, the encoded features are not suitable to input to the subsequent object detector. To address this challenge, we propose the MuRF-Net with a multi-receptive field voxelization mechanism to capture both contextual and local information. After the voxelization, the voxelized points (pillars) are processed by a feature encoder, and a channel-wise feature reconfiguration module is proposed to combine the features with different receptive fields using a lateral enhanced fusion network. In addition, to handle the increase of memory and computational cost brought by multi-receptive field voxelization, a dynamic voxel encoder is applied taking advantage of the sparseness of the point cloud. Experiments on the KITTI benchmark for both 3D object and Bird's Eye View (BEV) detection tasks on car class are conducted and MuRF-Net achieved the state-of-the-art results compared with other voxel-based methods. Besides, the MuRF-Net can achieve nearly real-time speed with 20Hz.
Philosophy at the Gym

The National Teaching & Learning ForumVolume 29, Issue 6 p. 6-8 Speaking From Experience Philosophy at the Gym Erik Kenyon, Erik KenyonSearch for more papers by this author Erik Kenyon, Erik KenyonSearch for more papers by this author First published: 12 October 2020 https://doi.org/10.1002/ntlf.30255Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume29, Issue6October 2020Pages 6-8 RelatedInformation
Person Re-Identification by Scalable Manifold Ranking with User Side Information Enhancement in Surveillance System

The goal of person reidentification (Re-ID) is to identify a given pedestrian from a network of nonoverlapping surveillance cameras. Most existing works conventionally rely on labelled pairwise data to learn a task specific distance metric for ranking. The value of unlabelled gallery instances is generally overlooked. On the other hands, Manifold Ranking (MR) has been successfully applied to Person ReID due to its ability to discover underlying geometrical structure of dataset given the query data. However, one problem of MR is that it cannot be scalable to large-scale data. To solve this problem, we develop a new scalable manifold ranking method for Person ReID by adopting an anchor graph for construction, where each data point is first to find the k neighbors of anchor points, and then the graph is constructed by the inner product of coefficients between the data points and anchor points. As a result, the proposed method can well handle a database with large-scale person images and do the online retrieval in a short time. Extensive evaluation is conducted on three benchmark datasets.
Geology, ore mineralization and geochemistry of Sorkheh sedimentary copper occurrence, northwest of Marand, NW Iran

Geology, ore mineralization and geochemistry of Sorkheh sedimentary copper occurrence, northwest of Marand, NW Iran
Real-Time Camouflage Gait Detection Model Based On Apache Spark Streaming

A real-time camouflage gait detection model is proposed. The model uses model-based feature representation. For mitigating the variation of the gait cycles, DTW Barycenter Averaging (DBA) is introduced to compute the average feature of the successive gait cycles. Using the Dynamic Time Warping (DTW), the model is capable of camouflage gait detection. Apache Flume and Spark Streaming are used for real-time processing. The model is evaluated using two Kinect gait datasets. Results showed that the proposed model is effective for real-time gait sequences processing, and it has an acceptable accuracy of camouflage detection.
FairFaceGAN: Fairness-aware Facial Image-to-Image Translation.

In this paper, we introduce FairFaceGAN, a fairness-aware facial Image-to-Image translation model, mitigating the problem of unwanted translation in protected attributes (e.g., gender, age, race) during facial attributes editing. Unlike existing models, FairFaceGAN learns fair representations with two separate latents - one related to the target attributes to translate, and the other unrelated to them. This strategy enables FairFaceGAN to separate the information about protected attributes and that of target attributes. It also prevents unwanted translation in protected attributes while target attributes editing. To evaluate the degree of fairness, we perform two types of experiments on CelebA dataset. First, we compare the fairness-aware classification performances when augmenting data by existing image translation methods and FairFaceGAN respectively. Moreover, we propose a new fairness metric, namely Frechet Protected Attribute Distance (FPAD), which measures how well protected attributes are preserved. Experimental results demonstrate that FairFaceGAN shows consistent improvements in terms of fairness over the existing image translation models. Further, we also evaluate image translation performances, where FairFaceGAN shows competitive results, compared to those of existing methods.
Modern Libraries as Exemplified by Central Scientific and Technical Library for Construction and Architecture

The experience of the Central Sci-tech Library for Construction and Architecture in providing user services based on their inquiries, interests and goals with the focus on the most demanded services is discussed. The key goals aimed at revising activity formats and user-library interaction are examined.
TruPercept: Trust Modelling for Autonomous Vehicle Cooperative Perception from Synthetic Data.

Inter-vehicle communication for autonomous vehicles (AVs) stands to provide significant benefits in terms of perception robustness. We propose a novel approach for AVs to communicate perceptual observations, tempered by trust modelling of peers providing reports. Based on the accuracy of reported object detections as verified locally, communicated messages can be fused to augment perception performance beyond line of sight and at great distance from the ego vehicle. Also presented is a new synthetic dataset which can be used to test cooperative perception. The TruPercept dataset includes unreliable and malicious behaviour scenarios to experiment with some challenges cooperative perception introduces. The TruPercept runtime and evaluation framework allows modular component replacement to facilitate ablation studies as well as the creation of new trust scenarios we are able to show.
LLS Home: I'd like to talk to someone: Home

A guide to the different ways you can get in contact with the Library and Learning Services teams
HAPPINESS IN THE CELEBRATION OF CHINESE NEW YEAR

Gong xi facai is a Chinese New Year greeting that is commonly spoken, heard, and written by people. Even if we don't know what it means, we guess the meaning must be good. The problem is what is the meaning of each word and the meaning of the sentence as a whole so that it can be concluded that the sentence is an expression of a joyful? Are there no other feelings? Since the sentence is considered a text, it will be examined which words express emotion, what kind of emotions they are. The goal is to express clearly what is meant by that sentence. To find out what kind of emotions it contains, Santangelo's theory (2000) will be used to detect which words express emotion and belong to which class. The data are Chinese Lunar New Year greetings written in Han characters. There is Indonesian-language data in the form of Chinese New Year pantun. Based on the analysis of the meaning components of emotions, the data are classified into several domains, such as Chinese New Year greeting, success in business, health, family, education, etc. The novelty of this research is to analyze the meaning components of emotional sentences so that emotional content can be identified precisely. This research will enrich research on emotions in the field of greetings for the Chinese New Year that has not been done much.
Fusus : a workflow to transform Arabic classical works in printed form to structured text

# This is a workflow that transforms scanned pages into readable text. The pages come from several printed Arabic books from the past few centuries. The workflow takes care of cleaning, OCR and postprocessing. A user can copy and paste image fragments of specks and symbols that must be removed before doing OCR. The workflow detects column layout and line boundaries. Individual lines will be passed to the OCR engine, which is Kraken using a model trained on many printed Arabic books. See [model](https://among.github.io/fusus/about/model.html). The result is stored in tab-separated files, with the transcription computed by the OCR step, plus position and confidence info resulting from that same step. The workflow can generate proofing pages that support manually checking the OCR results. # Next steps Once we have scanned a significant amount of pages, we'll construct a dataset in [Text-Fabric]() format out of it, with features that preserve positions of the words on the page and their confidence. From there we can implement steps to correct OCR mistakes and to perform intertextuality research between the ground work (the Fusus by Ibn Arabi) and its commentary books. # Authors This is work done by Cornelis van Lit and Dirk Roorda. There is more documentation about sources, the research project, and how to use this software in the [docs](https://among.github.io/fusus/).
A Distributed Seismic Exploration System Based On Beidou Positioning And Timing

A distributed seismic exploration system based on Beidou positioning and timing is designed in this paper. The system uses the function of wireless communication network, the Beidou short message in seismic exploration application and other technologies divided the exploration equipment into host and slave mode. With the host as the center, send data from the machine to the remote data analysis center via Beidou short message and carry out realtime geological data analysis and interpretation. Thus, it reduces the cost and construction difficulty of seismic exploration equipment, avoids the blind area of mobile base station, and is not restricted by desert, gobi desert and other sparsely populated a
Communication management for reliable service based IoT systems

Internet of Things (IoT) systems are becoming more and more popular. Moreover, service-based approach to IoT systems development is practically a standard utilized in their architecture. uti. IoT communication problems ware discussed in many articles about wireless communication, sensor networks or cloud computing. However the topic of high-level end to end communication in IoT systems is much less often the point of researchers' interest. Despite that, the reliability of communication makes much more sense especially when it is considered at the application layer. Furthermore, networks utilized in IoT systems are usually virtual and software-based. Due to this fact, it is reasonable to take consider this problem with a novel and adequate approach, rather with classical models of communication resource allocation. In this article authors presented an idea of reliable communication management for IoT systems based on resource allocation. This idea is discussed in context of service-based IoT system lifecycle, especially considering the stages of resource allocation and services execution. Concerning the presented concept, three algorithms were prepared and tested in the simulation process.
The Simplest Examples

Dynamical means moving and changing, active, so a dynamical system is an actively changing system of particles, points, or sets. Before turning to examples, we recall the origins of the subject, namely statistical mechanics. This subject came into existence because of the complexities of the mechanical laws in a system with many particles, such as gas.