Reviewerly/exHarmony huggingface dataset:
Attentive representations for objects detection and instance segmentation

Author(s): Wang, Xudong | Advisor(s): Vasconcelos, Nuno M | Abstract: In this thesis, we focused on investigating novelty modules integrated into popular detection network for assisting it to learn attentive representations for several practical applications in objects detection and instance segmentation tasks, including universal object detection and 3D medical image segmentation tasks. For universal object detection task, despite increasing efforts on universal representations for visual recognition, few have addressed object detection. In this thesis, we develop an effective and efficient universal object detection system that is capable of working on various image domains, from human faces and traffic signs to medical CT images. Unlike multi-domain models, this universal model does not require prior knowledge of the domain of interest. This is achieved by the introduction of a new family of adaptation layers, based on the principles of squeeze and excitation, and a new domain-attention mechanism. In the proposed universal detector, all parameters and computations are shared across domains, and a single network processes all domains all the time. Experiments, on a newly established universal object detection benchmark of 11 diverse datasets, show that the proposed detector outperforms a bank of individual detectors, a multi-domain detector, and a baseline universal detector, with a 1.3 parameter increase over a single-domain baseline detector. For 3D medical images segmentation tasks, although high resolution 3D medical images offer abundant detail information of human body parts and allow early detection of small lesions, due to the limitation of GPU memory, most methods either use down-sampled 3D volume as input, which significantly affects the detectability of small lesions, or use 2.5D networks to crop out neighboring image slices at original resolution, which loses context information along z direction. Both ways can significantly affect the performance of final model. In this paper, we propose a cross-slice spatial and channel attention module, which can maintain spatial resolution of input data, and effectively utilize context information along z direction of 3D volume. In order to get higher quality mask prediction, a cascade mask refinement module is designed to provide an objectiveness pixel-wise attention map for input feature maps. Furthermore, our scheme allows us to utilize the pretrained 2D detection models to achieve good results even with limited amount of training data, which is often met in medical applications and imposes big challenge to many deep learning methods. By utilizing the two novel modules, we achieve state-of-art performance 74.10 dice per case on Liver Tumor Segmentation Challenge(LiTS), which outperforms previous year challenge winner by 6.7 points and rank as 1st on leader board of LiTS benchmark upon submission of this paper.
Personality-oriented technologies for the formation of professional and artistic competence among students-future artists of monumental painting

This article examines the technologies for the formation of professional and artistic competence among students - future artists of monumental painting in the context of a personality-oriented approach. This issue is directly related to improving the quality of vocational education through the introduction of relevant pedagogical technologies. It also describes the characteristic features of student-centered classes in universities with students - future artists of monumental painting. The types of pedagogical technologies of the personality-oriented approach are given. The most relevant personality-oriented technologies are considered separately, and their effectiveness (or ineffectiveness) is confirmed by a pedagogical experiment conducted with students by future artists of monumental painting of the Krasnodar State Institute of Culture. And also the study of pedagogical literature describing the experience of predecessors on this topic. The role of various pedagogical approaches in the system of higher professional education is revealed and updated, their individual elements, which are especially significant for research, are highlighted. The author compares the opinions of various scientists (both practitioners and theorists) who have studied the personality-oriented approach in education and the technologies used in the context of this approach, on the basis of which a comprehensive conclusion is drawn, reflected in the concluding part of the article.
Movie Review System using Sentiment Analysis and Social Networking Platforms (SNPs)

Today online social networking platforms SNPs have become an integral part of or life where we share a lot of information of all the things, we do in life from shopping to movie watching. With ever growing use of SNPs recommendation systems have emerged as a hot trend for applications in e-commerce and digital media. These recommendation systems are useful as well as misguiding. Today digital media use has increased tremendously with increase in internet speeds. But users do not get proper review of a movie and a user is lured to watch a substandard movie which he does not intended to do, thus costing a user time and money. So, there is a need of developing a movie review which will give correct reviews of a digital content like movies so he can only movies which he intends to do. So, we are studying various techniques authored by various authors and create a good movie review system of our own. The first technique we studied and intends to use is movie recommendation system using tweets. The second study is movie recommendation using similarity measures. The third study does find a public shamming using SNP. These techniques are useful and we propose to use some part of each in our new movie review framework by improving the techniques drawbacks. The new framework will be a combination of data from more than one SNP and using natural language processing and machine learning on the data. We are going to use two machine learning algorithms SVM and Naïve Bayes for this purpose. For natural language processing of SNP data, we are going to use OPEN-NLP. We intend to use SNPs such as Twitter and any other movie database like IMDB etc. for data on the movie. The movie will be classified in three classes bad, good and excellent. The results from each algorithm SVM and Naïve bayes will be analyzed for each SNP and try to give user a more accurate movie review by combining all the reviews together and classes accuracy and show overall prediction results with a rating. To get more accurate results for each movie we are going to create a dataset for each movie for demonstration and will not depend on a single combined dataset as keywords for each movie may be different. We are going to combine datasets for each movie from multiple SNPs.
EventNarrative: A Large-scale Event-centric Dataset for Knowledge Graph-to-Text Generation

We introduce EventNarrative, a knowledge graph-to-text dataset from publicly available open-world knowledge graphs. Given the recent advances in event-driven Information Extraction (IE), and that prior research on graph-to-text only focused on entity-driven KGs, this paper focuses on event-centric data. However, our data generation system can still be adapted to other other types of KG data. Existing large-scale datasets in the graph-to-text area are non-parallel, meaning there is a large disconnect between the KGs and text. The datasets that have a paired KG and text, are small scale and manually generated or generated without a rich ontology, making the corresponding graphs sparse. Furthermore, these datasets contain many unlinked entities between their KG and text pairs. EventNarrative consists of approximately 230,000 graphs and their corresponding natural language text, 6 times larger than the current largest parallel dataset. It makes use of a rich ontology, all of the KGs entities are linked to the text, and our manual annotations confirm a high data quality. Our aim is two-fold: help break new ground in event-centric research where data is lacking, and to give researchers a well-defined, large-scale dataset in order to better evaluate existing and future knowledge graph-to-text models. We also evaluate two types of baseline on EventNarrative: a graph-to-text specific model and two state-of-the-art language models, which previous work has shown to be adaptable to the knowledge graph-to-text domain.
In-service supervision of a beginning teacher as a condition for the continuity of professional development

The article is devoted to the problem of organizing in-service supervision of a beginning teacher in educational environment. The conceptual and practical ways of designing the model of in-service supervision of a young teacher are analyzed in the article. In-service supervision is defined as a purposeful complex process involving the cooperation of teachers-mentors with a young specialist in order to ensure successful entry into the profession, effective teaching, adaptation to the professional environment and overcoming crises and barriers arising in the process of teaching. The model of in-service supervision is based on a convention generation approach. A set of complementary principles of organizing in-service supervision is described. The model of in-service supervision is founded on the institution of double mentoring: a mentor from teachers’ education university staff and a mentor from school supervise a beginning teacher. The in-service supervision is based on mentoring technology. The authors describe the developed website for online in-service supervision, allowing timely, prompt interaction with a young teacher. The article analyzes the system of criteria for choosing a mentor as well as the system of professional and personal qualities of a mentor.
Reading Aloud to Increase Parental Engagement in Children Literacy during the Covid-19 Pandemic

The parental engagement of the 1st graders of SD Ihsaniyah Gajahmada Tegal in their children’s early literacy phase is still not maximal. Reading has not become an important part of learning activities at home. Therefore, efforts must be made to encourage parents to pay more attention to children's reading interest by being directly involved in children’s reading activities. The reading aloud activity aims to arouse parental awareness and provide skills for parents of the 1st graders of SD Ihsaniyah Gajahmada Tegal to be able to accompany their children in reading books at home as an effort to develop reading interest from an early age. Materials and demonstration of reading aloud were delivered via podcast and broadcast on Youtube due to social restrictions during the Covid-19 pandemic. Then, parents practiced reading aloud to their children at home. This activity was recorded and the video was sent to the service team for feedback and evaluation. Through this activity, parents could spend their time to assist their children in learning, especially reading. Children learned with enthusiasm and had a pleasant book reading experience. In addition, students' interest in reading will grow because they get a pleasant impression from reading aloud with their parents at home.&#x0D; &#x0D;
Cryptocurrency - Illusion vs Solution

The pros and cons regarding the use of cryptocurrency in supporting or - in the extreem – replacing conventional currency (fiat) is still going on. More than 2 decades of its born, still there are more government in the cons position than in favor of the use of cryptocurrency. This paper explored the cryptocurrency as to be one of many aspects in deciding whether it would be positioned as an illusion or to be a solution for a nation’s economy. This paper also portrait cryptocurrency from the accounting point of view. As the financial information provider, accounting is important for fundamental decisions in economy because of its nature to be conservative. The ultimate goal is that this could be one of many sources to help Indonesian government in deciding how to best deal with cryptocurrency.
Face Mask Detection System

The World Health Organization (WHO) reports suggest that the two main routes of transmission of the COVID-19 virus are respiratory droplets and physical contact. Wearing a medical mask is one of the prevention measures that can limit the spread of certain respiratory viral diseases, including COVID-19. Therefore, it is necessary to wear a mark properly at public places like supermarkets, shopping malls. In this paper we propose a Face Mask Detection system to check whether a person is wearing a mask properly or not. There are only a few researches on face mask detection in video streams. It consists of a two phase architecture for detecting face masks and will be using OpenCV, Tensorflow/Keras and Deep Learning to achieve high accuracy.
Visualizing the Data

In the previous chapter, we discussed a number of steps involved in preparing the data for analysis. Before analyzing the data, it is imperative to get to know the nature of data we are dealing with. Visualizing the data may give us some useful insights about the nature of data. These insights, such as patterns in the data, distribution of the data, outliers present in the data, etc., can prove to be handy in determining the methodology to be used for analyzing the data. In addition, visualization can be used at the end of analysis to communicate the findings to the party concerned as conveying the results of analysis through visualization techniques can be more effective than writing pages of textual content explaining the findings. In this chapter, we will learn about some of the basic visualization plots provided by the Matplotlib package of Python and how those plots can be customized to convey the characteristics of different data.
Cognitive Task Analysis to Improve Student Competencies: a Pilot Study based on the Use of the Square of PErceived ACtion Model

The aim of this pilot study was to test a method developed in the Cognitive Task Analysis paradigm for adult occupational training in the field of education. The method used was based on the Square of Percieved ACtion (SPEAC) protocol using the SPEAC model (explaining how to successfully put competencies in action). The study was conducted in two secondary education classes, with a sample of 36 students (control group and test group) for an activity in Economics &amp; Social science. The application of this innovative SPEAC-based method resulted in a significant and homogeneous increase in student performance. Beyond showing that the protocol can be applied both for adults and the young and in both occupational and academic contexts, the study demonstrates the benefits in learning and training with this method. Cognitive processes underpinning the improvement in teaching and limitations of the method are discussed.
Low Light Image Enhancement using Convolutional Neural Network

Great quality images and pictures are remarkable for some perceptions. Nonetheless, not each and every images are in acceptable features and quality as they are capture in non-identical light atmosphere. At the point when an image is capture in a low light state the pixel esteems are in a low-esteem range, which will cause image quality to decrease evidently. Since the entire image shows up dull, it's difficult to recognize items or surfaces clearly. Thus, it is vital to improve the nature of low-light images. Low light image enhancement is required in numerous PC vision undertakings for object location and scene understanding. In some cases there is a condition when image caught in low light consistently experience the ill effects of low difference and splendor which builds the trouble of resulting undeniable level undertaking in incredible degree. Low light image improvement utilizing convolutional neural network framework accepts dull or dark images as information and creates brilliant images as a yield without upsetting the substance of the image. So understanding the scene caught through image becomes simpler task.
Best Wrist Rest For Laptops

A wrist rest can be an essential accessory for users of keyboards. Just in case you’ve been wondering if you can use a wrist rest on your epic laptop, ...
An agent and web services based e-government model validation

In e-government, the provision of valuable services depends upon the capacity of public administrations to coordinate their services. Different digital government solutions have been developed. Unfortunately, most of these works assume that all the involved partners are equipped with sophisticated information technology (IT) infrastructure, which limits their applicability especially in developing countries where the administrations are usually under equipped. Moreover, many of the proposed solutions introduce centralised coordination methods that do not comply with the distributed nature of public administrations. This paper presents an e-government model based on agent and web services. It introduces an inter-organisational workflow (IOW) model based on the idea of interfacing. The e-government entities (GEs) are only required to describe their services using WSDL, they are distributed and interact directly with no need of a middleware. Two different case studies are carried out to demonstrate the applicability of our approach.
GOALS OF PEDAGOGICAL RESEARCH

The article is aimed at theoretical understanding of the goals of pedagogical research. It presents a historical excursion into the study of the problem of goal-setting in philosophy. The author analyses the definitions of the concept “goal” in the context of pedagogy. The typology of the goals of pedagogical research is given.
Design of Spatio-temporal Data Archival for Big-data Satellite Imagery: Use Cases

This research article emphasizes the importance of production data systems in parallel and distributed spatial databases. It proposes a Multi Protocol Label Switching (MPLS) computer network design based on virtual desktop infrastructure (VDI), local area network, for performing complex workflows using spatio-temporal datasets such as Worldview-3, Sentinel-3, and Landsat-8 satellite imagery. The main intent is to facilitate a workflow processing procedure that will automatically devise a sequential and ordered flow of machine instructions in a pipelined approach with robust data redundancy and feature retrieval procedure. In addition, the research article implies that a spatial design pattern such as model-view-controller (MVC) can be designed and implemented using geographic markup language (GML) and OGC based webservices. In addition, a proprietary customized algorithm will be designed to perform geospatial analysis and archival of bigdata.
Indo Map Rework [1.31-1.35]

Changelogs: Compatible for Euro Truck Simulator 2 patch 1.31-1.35 Improved coastal roads in Southern Island (from Hajisari to Pradasari) Improved ...
A Bibliometric Analysis of Authorship Productivity and Collaborative Research in Blogosphere

An analysis of 718 publications published by social area on Blogosphere during 2002-2018 and indexed by web of science online Database indicates that the publication output in the Global Research Publications. The highest numbers of papers were published during the year 2010 and 2013 with 76 records, the followed by 72 papers in 2009, 69 papers in 2015 and 67 records of the publication in the year 2011. The least number of publication in the years 2002, 2003 and 2004 with only one record of the publications due to the initial stage of web developments. Overall, 1368 authors contributed 520 publications in the journal and institutions with 668 records of the articles. Contribution of journals, ranking of authors, preference of publication and frequency of keywords were also analysed in this paper.
Detecting Lexical Semantic Change across Corpora with Smooth Manifolds (Student Abstract)

Comparing two bodies of text and detecting words with significant lexical semantic shift between them is an important part of digital humanities. Traditional approaches have relied on aligning the different embeddings using the Orthogonal Procrustes problem in the Euclidean space. This study presents a geometric framework that leverages smooth Riemannian manifolds for corpus-specific orthogonal rotations and a corpus-independent scaling metric to project the different vector spaces into a shared latent space. This enables us to capture any affine relationship between the embedding spaces while utilising the rich geometry of smooth manifolds.
“SAVE” – An Integrated Approach of Personal and Home Safety for Active Assisted Living

The paper presents the concept and demonstrator of “SAVE – SAfety of elderly people and Vicinity Ensuring”, an integrated approach of personal and residential security. This AAL (Active Assisted Living) system aims to support elderly end-users staying in their familiar home and surroundings for as long as possible, being safely and permanently in contact with their caregivers. The top-down Universal Modeling Language (UML) service orientation enabled a unified co-design of both human and machine communications. Furthermore, the present concept includes an integrated subscription mechanism for people and devices, in a multi-tier user structure and a central-local distributed processing (Cloud-Edge). There are presented the end-user perspective, selection and involvement (in pilot prototyping of the SAVE demonstrator), considering cognitive age-related issues, oriented on usability and on the functional specifications of interfacing via web-apps (independent of the mobile platforms operating system). Location Based Services (LBS) manage data from the Geographical Information Systems (GIS) in a unified modern way, based on LISP – Location - (from) Identity Separation Protocol. These services of “orientation” – localization, real-time tracking – are integrated with another aspect of “restoring the referential” (both personal and communitarian): (re-) planning service, improving alert information in case of emergency, bilateral push-pull of security notifications. Restoring the end-users well-being takes benefit of eHealth and actigraphy services. The other approach, bottom-up, is based on micro-services software/netware implementation, modern smartwatches/smartphones and wearable devices, leveraging their programmability and multi-modal and multi-range (near-field or cellular) communications.
PEMBANGUNAN KAWASAN PEMUKIMAN DENGAN KONSEP KEBENCANAAN DI KABUPATEN BOGOR

Bogor Regency as an area that is a buffer for the capital city of Jakarta is an alternative choice that is very popular considering some of the ease of available facilities ranging from transportation facilities, beauty, and natural beauty including the availability of large enough land for settlement. In addition to saving a million charms to become a residential area, Bogor Regency is also one of the areas prone to landslides and floods. In order to meet the need for settlements, it is necessary to apply the concept of disaster by considering all risks that may occur technically and regulations by taking a preventive approach consistently during the planning of the settlement development. The method used by the author in this study is a qualitative method with a literature study design and a phenomenological approach. The results show that some settlements have not fully implemented the concept of disaster as a conscious and anticipatory effort in minimizing disaster risk so that safe and comfortable conditions arise for their residents, in addition to achieving community welfare in order to improve national security.