Reviewerly/exHarmony huggingface dataset:
Il glossario latino-bergamasco (sec. XV) della Biblioteca Universitaria di Padova (ms. 534)

The 15th-century ms. 534 of Biblioteca Universitaria di Padova (Italy) contains an extensive Latin-Bergamasco glossary, known through its 1893 edition prepared by the German scholar Jean Etienne Lorck. This publication offers a new edition of this text, based on 21st-century editing principles and standards, and helps gain valuable new insight into the broad linguistic and lexical material the glossary preserves.
The Aquaponic Ecosystem Study as a Base of Applied Research in Bioinformatics

This article is an enhancement of the authors chapter "Critical Review about Aquaponics is non-boring sciences, as a base of competence" about conceptual platform for the work of a network of regional experimental sites that work out various aspects of the implementation of design and research activities in the study of aquaponics.The chapter contains a description of the experience of creating a new component of the regional education system "Aquaponics in Education", the construction of the content of education in the educational organization, taking into account the new component; Designing a unified network of interaction between educational organizations of various types for the implementation of the author's experimental program "The Academy of non – boring Sciences. Aquaponics ". Methodical recommendations on the inclusion of innovative equipment Fish Plant Family Unit and Fish Plant Production in the educational system, the direction of design and research activities of students in the field of aquaponics are proposed.
LibGuides: Reference Training: Tiered Reference: 6. How to Use the Knowledge Base "Ask The Library" / FAQs

This guide will help train Library Assistants to respond to basic reference questions, record/track responses and introduce the libchat tool.
Information Extraction of the Aerodrome Hazardous Weather Warning via Deep Learning

The bad weather would affect the operation of airport. Improving capability of weather information detection can guarantee efficient operation of airport. Some air traffic management systems are able to extract the weather information from the radar signal. Some kinds of text include weather information during actual operations, such as aerodrome hazardous weather warning. Current ATM systems cannot process texts due to unstructured characteristics. Compared with radar signal, the aerodrome hazardous weather warning consists of human’s prior experience, which is more useful in application of situation awareness. This paper proposes a deep-learning approach for weather information extraction, which can improve the capacity of aerodrome hazardous weather warning information extraction. The method applies the named entity recognition model to extract the information such as weather type, weather state, speed and direction of wind, starting and end time, etc.
Meningkatkan Kemampuan Membaca Pemahaman Melalui Media Mind Mapping Bagi Anak Tunarungu (Single Subject Research Kelas VIII di SLB N 1 Painan)

Every individual has the same right in obtaining an education, without exception, including children with special needs. One of the children with special needs is a deaf child. Deaf children are children who experience obstacles in the ability to hear which causes children to experience an obstacle in language development caused by the malfunction of all or part of their hearing apparatus. Researchers have an interest in raising this issue because they want to help children improve their reading comprehension skills.This study aims to prove the effectiveness of mind mapping media in improving reading comprehension skills in answering questions in the form of 5W+1H (What, Who, Where, Why, When and How) for deaf children in class VIII at SLB N 1 Painan. This study uses an experimental research in the form of Single Subject Research (SSR) with an A-B-A design. The data analysis technique is in the form of graphic visual analysis.The results of data analysis carried out for 17 meetings, which were in three conditions, namely baseline (A1) with the acquisition of percentage results, namely: 30%, 40%, 20%, 20%, 20%. In the intervention condition (B) with the acquisition of percentages: 70%, 60%, 80%, 80%, 90%, 90%, 90%. Finally, in the baseline condition (A2), the percentage gains are: 90%, 80%, 90%, 90%, 90%. The results of this study indicate that the ability to read comprehension increases after using mind mapping media for deaf children in class VIII at SLB N 1 Painan.
LibGuides: System Wide Holds - Training Guide: Guide Overview

The purpose of this guide is to provide staff a reference resource for processing Requests and Holds on NLPL materials. A general overview of the System-wide Holds initiative.
Real-time Semantic Segmentation Based on Multi-scale Feature Map Joint Pyramid Upsamping

Vision-based perception is an import link in driverless technology, and semantic segmentation is one of the mostly uses atrous convolution with a large amount of computation and high memory consumption to extract high-resolution feature maps. As a result, the current mainstream semantic segmentation network lacks the segmentation speed and cannot be effectively applied in driverless technology. To solve this problem, a semantic segmentation network with better real-time performance is proposed. Firstly, a lightweight convolutional neural network is used as the encoder, and stride convolution and regular convolution are used to replace the time-consuming and memory-consuming atrous convolution. Secondly, in order to obtain the feature map similar to Deeplab v3+, a new joint upsampling module, Multi-scale Feature Map Joint Pyramid Upsamping(MJPU), is proposed. By fusing multiple feature maps in the encoder, a high resolution feature map with richer semantic information is generated. Experments on the Cityscapes dataset show that, compared with the popular semantic segmentation network Deeplab V3+, the proposed network can improve the segmentation speed to 31.4 FPS/s without losing a lot of performance(mIoU of 44.03%). Therefore, the network proposed in this paper has better real-time performance and is more suitable for driverless scenes.
ONLINE TEACHING – TOOLS & STRATEGIES

Facilitating an online teaching amongst today’s learners requires an educator to be innovative and creative and to have an effective online existence. In the current online learning environment (otherwise called e-learning), keeping learners insightfully connected with and motivated while alloting the necessary course content requires educators empowering a protected, non-judgmental environment whereby perspectives, points of view, and individual and expert experiences are encouraged. The educator must exhibit a learner centred learning process, where students are held answerable for their active participation and self-directed learning while balancing a facilitator role to further upgrade the learning interaction. This article investigates one teacher's intelligent practice measure that has been created over various years as an early adopter of online education. It will explore the organizational aspect of teaching-facilitating a dynamic robust online course.Keywords: transformative teaching, educator reflection, online education, e learning, blended learning, online teaching
Frequency-domain evaluation of light source and sensor interactions in photoelastic fringe patterns

The interactions between light sources and sensors alter the spatial frequency content of fringe patterns in photoelasticity studies. This paper presents a computational strategy to evaluate these alterations in the frequency domain.
Implementing Face Search Using Haar Cascade

It is a known fact that human beings are able to distinguish distinct people primarily by observing the human face. Visual search engines are the ones that, when given the name, search for celebrity faces in a video file. This will be retrieval based on the data related to the file. The goal of this paper is to enhance the usability of video searches. Users would be able to input a video and a picture (passport size) of the person they are intended to search for, and then select the frames containing the given image from the uploaded file. This would be helpful for video capture purposes. This is especially useful for the people who are interested in a part of the video in which either they themselves or the person of their interest is available. This is achieved by removing all frames from the video and saving the extracted video in different directories. Facial detection method is used to recognize the faces in the frame, and these identified frames are used as training models for the next level of facial recognition. The facial recognition technique is used to differentiate the reference image from all the frames, to transform the selected frames to a video, and to play it for the user. This application faces many challenges like occluded face detection and recognition. Also, frontal view of the face will be necessary for this application to work successfully. These challenges can be taken into account as the future work for this particular application.
Loma Linda University Libraries: Citation Style Guide: Software, Printing, and IT Help

How to cite electronic documents in AMA, APA, MLA, and Chicago styles, plus links to further information on these style formats.
A video inpainting method for unmanned vehicle based on fusion of time series optical flow information and spatial information

In this article, the problem of video inpainting combines multiview spatial information and interframe information between video sequences. A vision system is an important way for autonomous vehicles to obtain information about the external environment. Loss or distortion of visual images caused by camera damage or pollution seriously makes an impact on the vision system ability to correctly perceive and understand the external environment. In this article, we solve the problem of image restoration by combining the optical flow information between frames in the video with the spatial information from multiple perspectives. To solve the problems of noise in the single-frame images of video frames, we propose a complete two-stage video repair method. We combine the spatial information of images from different perspectives and the optical flow information of the video sequence to assist and constrain the repair of damaged images in the video. This method combines the interframe information of the front and rear image frames with the multiview image information in the video and performs video repair based on optical flow and a conditional generation adversarial network. This method regards video inpainting as a pixel propagation problem, uses the interframe information in the video for video inpainting, and introduces multiview information to assist the repair based on a conditional generative adversarial network. This method was trained and tested in Zurich using a data set recorded by a pair of cameras mounted on a mobile platform.
Energy and Network Aware Mobile Augmented Reality

Author(s): Apicharttrisorn, Kittipat | Advisor(s): Krishnamurthy, Srikanth V. Dr. | Abstract: This dissertation has two main objectives -- solving power and latency issues in mobile augmented reality. For power, we showcase the power drain due to the two heaviest components -- simultaneous localization and mapping (SLAM) and deep convolutional neural networks (DNNs) and design solutions to reduce the power consumption on mobile devices. Our single-user solution is to use DNNs as needed, to detect new objects or recapture objects that significantly change in appearance, and otherwise depend on low-power object tracking. For multi-user solutions, we use peer-to-peer communications to exchange key information among devices, and finally assign roles to each of them -- primary or secondary. A primary device continuously tracks target objects and shares their information to slaves. Secondary devices do not need SLAM or DNN but leverage the shared information from the master and other lightweight methods to keep track of the objects with high precision, and thus significantly reduce power consumption. In addition, we can rotate the master functionality across participants in order to distribute energy expenditures among them and increase the longevity of the AR experience. For latency, we perform a first-of-its-kind measurement study on both public LTE and industry LTE testbed for two popular multi-user AR applications, yielding several insights such as: (1) The radio access network (RAN) accounts for a significant fraction of the end-to-end latency (31.2\%, or 3.9 s median); (2) AR network traffic is characterized by large intermittent spikes on a single uplink TCP connection, resulting in frequent TCP slow starts that can increase user-perceived latency; (3) Applying a common traffic management mechanism of cellular operators, QoS Class Identifiers (QCI), can help by reducing AR latency by 33\% but impacts non-AR users. Based on these insights, we propose AR solutions to intelligently adapt IP packet sizes and periodically provide information on uplink data availability, respectively. Our solutions help ramp up network performance, improving the end-to-end AR latency and goodput by ~40-70\%.
Las Artes Plásticas como estrategia didáctica, artística y creativa dentro de la escuela para la expresión de la violencia en niños de 3° y 4° de primaria de la Institución Educativa Llanos de Cuivá

ABSTRACT: This research work is carried out at the Llanos de Cuiva Educational Institution, with students in grades 3 and 4, whose objective is to apply a methodological strategy mediated by the plastic arts for the expression of violence, reflected in the school environment. It uses qualitative research with an action-participation approach, in which children, through their artistic creations, become important members of this project, observation guides, interviews and surveys of direct and indirect population, workshops and exhibitions of the work done by the students, in which relevant aspects were analyzed. This work seeks to provide a didactic and creative tool to identify and treat cases of violence in children, through the plastic arts. In addition, it ontribute to a treatment from the arts and pedagogy for all people who are related to the artistic, educational, or person who is interested in knowing more about this problem, it is a work that can help future research on said phenomenon. It was concluded that the arts served the children to make catharsis, express and release the painful things of life, all calamity and violence, in addition to the children significantly improving their coexistence inside and outside the school environment.
Learnable weight initialization in neural networks

A new method of initializing the weights in deep neural networks is proposed. The method follows two steps. First, consider each layer as a model and perform a linear regression to keep the mean of the layer output to zero and variance after the data is passed through the activation function to one. Once each layer converges to the target mean and variance, initialize the weights of the original model with the learned weights. Performance is evaluated on LeNet and ResNet18 architectures on FashionMNIST and Imagenette datasets. The activation functions used to analyze the performance are sigmoid, tanh and ReLU. Findings show that the learned weights can perform similarly, and for certain scenarios, better than the different types of weight initializers used frequently in the field of deep learning. It is important to mention that this method requires the weights to be learned independently of the training of the model. Thus, there is a small time overhead. Moreover, it is required to adjust the hyperparameters(learning rate, epochs etc) to find the optimal weights. The findings from this thesis can be used in the future to better understand how the gradient flow could be controlled through the network and finding a more generic approach towards the vanishing and exploding gradient problem. The method requires to learn the weights followed by training the network. Learning the weights involves tweaking the hyperparameters(learning rate, number of epochs, etc). For future work, these aspects could be automated for the optimal performance of the network.
IFLA Special Interest Group (SIG)on Library Publishing: 2019 Midterm Meeting

“The aim of the event was to bring together a broad spectrum of publishing programs, to exchange knowledge,and to foster networks and mentoring relationships among library publishers at all stages, also highlighting theimportant role that the Library Publishing Coalition plays in this regard. “ As our Library is embarking on theMaynooth Academic Publishing venture, it was essential for my colleague Fiona Morley (Head of DigitalProgrammes and Information Systems) and myself (Library Technician & IR Manager) to attend and hear the latesttrends and the advice from our global counterparts.
STRATEGIES FOR CONTROLLING PEER GROUP INFLUENCE ON STUDENTS’ CLASSROOM BEHAVIOURS OF SECONDARY SCHOOL STUDENTS IN AGUATA LOCAL GOVERNMEMT AREA.

The study was carried out on strategies for controlling peer group influence on students’ classroom behaviours of secondary school students in Aguata Local Government Area. The purpose of the study was to assess strategies for controlling peer group influence on students’ classroom behaviours. Two research questions were formulated to guide the study. Descriptive survey research design was used. The population of the study was 646 teachers and the sample was 200 respondents chosen through simple random sampling technique. The questionnaire with ten items was the instrument used for data collection. The reliability of the instrument was determined using test-retest technique. The score of the two tests were correlated and the reliability coefficient value of 0.71. The questionnaire with 10 items was distributed to the respondents by the researcher and his assistants who also collected the copies of the questionnaires when they were filled. The data obtained was analyzed using mean rating. The study found amongst others that verbal instruction and instructional supervision are used as means of controlling negative peer group influence on students behaviours. Based on the findings it was recommended among other things that teachers should be trained on maximizing the use of verbal instruction and instructional supervision as strategies for controlling peer influence in schools.
Comparing Neural Network Models for Photovoltaic Power Generation Prediction

Research on alternative energy sources has been increasing for the past years due to environmental concerns and the depletion of fossil fuels. Since photovoltaic generation is intermittent, one needs to predict solar incidence to alleviate problems due to demand surges in conventional distribution systems.Many works have used Long Short-Term Memory (LSTMs) to predict generation. However, to minimize computational costs related to retraining and inference, LSTMs might not be optimal. Therefore, in this work, we compare the performance of MLP (Multilayer Perceptron), Recurrent Neural Networks (RNNs), and LSTMs for the task mentioned above. We used the solar radiance measured throughout 2020 in the city of Maceió (Brazil), taking into account periods of 2 hours for training to predict the next 5-minutes. Hyperparameters were fine-tuned using an optimization approach based on Bayesian inference to promote a fair comparison. Results showed that the MLP has satisfactory performance, requiring much less time to train and forecast. Such results can contribute, for example, to improving response time in embedded systems.
Accounting Registration for E-Commerce Operations and Its Impact on Reliability of Accounting Information (Field Study in Pharmaceutical Industry Sector in Jordan)

The study aimed to identify the impact of the accounting registration of electronic commerce operations on the reliability of accounting information in pharmaceutical industry sector in Jordan. The study community is one of the 14 pharmaceutical industries companies operating in Jordan and a company operating in the pharmaceutical industry in Jordan and registered with the Pharmacists Syndicate either the companies were public joint stock or limited liability company, while the sample consisted of (121) respondents from financial managers, heads of accounting departments, and accountants working in these companies. The study found that there is an effect of the accounting measurement of e-commerce operations with variables (recognition of revenue, revenue acquisition, and revenue ability to verify, revenue verification) on the reliability of accounting information in companies operating in the pharmaceutical industry in Jordan. The study recommended checking the companies ’ability to perform revenue recognition and accounting registration treatments in the e-commerce operations so that they are compatible with the changes and developments in the use of technologies compatible with international accounting standards.
LibGuides: System Wide Holds - Training Guide: Daily Workflow

The purpose of this guide is to provide staff a reference resource for processing Requests and Holds on NLPL materials.
Unambiguous State Discrimination Attack on the B92 Protocol of Quantum Key Distribution with Single Photons

We consider an unambiguous state discrimination attack on the B92 protocol of quantum key distribution, realized on the basis of polarization encoding of photons produced by a single-photon source. We calculate the secure key rate and the maximal tolerable loss for various overlaps between two signal states employed in this protocol. We make also a comparison with a physically impossible attack of perfect quantum cloning, and show that the unambiguous state discrimination is much more dangerous for the B92 protocol, than this attack, demonstrating thus, that the security of quantum key distribution is not always based on the no-cloning theorem.
AI may help predict previously unseen states in dynamical systems

Machine-learning technique can infer long-term, stable behaviors from information about only one known attractor.
Cyberbullying on Social Networking Sites: The Crime Opportunity and Affordance Perspectives

Cyberbullying on social networking sites (SNS bullying) is an emerging societal challenge related to the deviant use of technologies. To address the research gaps identified in the literature, we d...