Reviewerly/exHarmony huggingface dataset:
Handwritten Annotation Spotting in Printed Documents Using Top-Down Visual Saliency Models

In this article, we address the problem of localizing text and symbolic annotations on the scanned image of a printed document. Previous approaches have considered the task of annotation extraction as binary classification into printed and handwritten text. In this work, we further subcategorize the annotations as underlines, encirclements, inline text, and marginal text. We have collected a new dataset of 300 documents constituting all classes of annotations marked around or in-between printed text. Using the dataset as a benchmark, we report the results of two saliency formulations—CRF Saliency and Discriminant Saliency, for predicting salient patches, which can correspond to different types of annotations. We also compare our work with recent semantic segmentation techniques using deep models. Our analysis shows that Discriminant Saliency can be considered as the preferred approach for fast localization of patches containing different types of annotations. The saliency models were learned on a small dataset, but still, give comparable performance to the deep networks for pixel-level semantic segmentation. We show that saliency-based methods give better outcomes with limited annotated data compared to more sophisticated segmentation techniques that require a large training set to learn the model.
Effective Techniques for Pedestrian Detection in Smart Autonomous Vehicles

Pedestrians are essential objects in computer vision. Pedestrian detection in images or videos plays an important role in many applications such as real-time monitoring, counting pedestrians at various events, detecting falls of the elderly, etc. It is formulated as a problem of the automatic identification and location of pedestrians in pictures or videos. In real images, the art of pedestrian detection is an important task for major applications such as video surveillance, autonomous driving systems, etc. Pedestrian detection is also an important feature of the autonomous vehicle driving system because it identifies pedestrians and minimizes accidents between vehicles and pedestrians. The research trend in the field of vehicle electronics and driving safety, vision-based pedestrian recognition technologies for smart vehicles have established themselves loudly or slowing down the vehicle. In general, the visual pedestrian detection progression capable of be busted down into three consecutive steps: pedestrian detection, pedestrian recognition, and pedestrian tracking. There is also visual pedestrian recognition in the vehicle. Finally, we study the challenges and evolution of research in the future.
Discussion on research capability of teachers in pedagogical universities/faculties to meet the requirements of the New General Education Curriculum 2018

The New General Education Eurriculum 2018 has had an impact on the teaching professionals in pedagogical universities/faculties; and the development of teachers’ research capability is absolutely vital in the reform context. The article outlines the significance and essential qualities of teachers in scientific research activities. On that basis, strategies to enhance research capability for teachers in pedagogical universities/faculties are suggested to meet the requirements of the New General Education Curriculum issued in 2018.
PiPo-Net: A Semi-automatic and Polygon-based Annotation Method for Pathological Images

Metastatic involvement of lymph nodes is one of the most important prognostic variables for many cancers. Several deep learning based algorithms have been developed to segment metastatic regions in pathological images to help predict prognosis. However, the training of these methods requires a large amount of annotated data, and the labeling task is an extremely time-consuming process for human annotators. In order to reduce the annotation burden, we for the first time propose a semi-automatic annotation method (PiPo-Net) for the labeling of pathological images. The method is comprised of two subnetworks, a pixel-wise segmentation network (Pi-Net) and a polygon-based annotation network (Po-Net). The Pi-Net adopts an improved encoder-decoder architecture and can effectively aggregate multi-scale image features. The Po-Net is built on the Pi-Net and leverages a two-layer recurrent neural network to generate tight-bounded polygons for the metastatic regions. Corresponding to the proposed network architecture, a loss function called PiPo-loss is introduced to help optimize the whole network. The main advantage of our method is that it integrates human annotators into the prediction loop, allowing to iteratively refine the predictions according to the suggestions from human annotators. We evaluate our method on Camelyon16 database and achieve a Dice score of 91% in the initial annotation attempt. We also demonstrate the effectiveness of the human-network collaborative annotation, which achieves promising labeling results, verifying the advantages of our proposed method.
Codex Fragments Detached from Incunabula in the Department of Manuscripts and Rare Books of the Library and Information Centre of the Hungarian Academy of Sciences

This article presents the results of a study of 37 manuscript fragments detached from incunables in the Department of Manuscripts and Rare Books of the Library and Information Centre of the Hungarian Academy of Sciences. The incunables themselves were imported into Hungary between the end of the eighteenth and early twentieth centuries.
A case study of the benefits of the IoT in the Qatari retail industry

Technological advancements have led to the creation of new paradigms like the Internet of Things (IoT). These technologies are moving the digital space into a period where they will power billions of devices leading to the transformations of products and services provided by businesses. Therefore, the main purpose of this study is to explore the benefits of deployment of the Internet of Things (IoT) in businesses using the case of the Qatari retail businesses. The study assumed an interpretivism research philosophical stance and an addictive approach to theory utilising the Technology, Organisation, Environment model to guide the research. The research data were gathered using a qualitative approach utilising semi-structured interviews as the method of data collection. Accordingly, the heads of information technology in the selected retail industry businesses in Qatar were interviewed to answer the main research questions. The findings uncovered that retailers in Qatar are using the IoT devices such as sensors, scanners, beacons, smart shelves, personalisation alerts, and FRIDs to enable their key business operations and processes. Even though the Qatar retail businesses are not concerned about the specific IoT devices utilised, the benefits of their deployment established from the study include automation of business processes (Technological benefits), efficiency and personalisation of customer requirements (Organisational benefits), and increased collaboration and supply chain optimisation within the entire Qatar retail industry (Environmental benefits). As such, the results of the study agree with the TOE model that technology, organisation, and environment are the driving forces behind technology adoption and utilisation. Finally, among practical implications, a collaboration between software developers and the retail industry project professionals will ensure that the IoT artefacts are designed with security mechanisms, thus enhancing the security and safety of the information gathered from the IoT devices. Further, the study offers guidance on the theoretical elements that contribute to the benefits of utilising the IoT in Qatar retail businesses.
Research on Integration Construction and Safety of Grounding System in Three-in-One Station

The integration of substation, energy storage station and data center grounding system is the key point in the construction of three-in-one station. Firstly, the change of ground potential rise (GPR) before and after the integration of the three-in-one station grounding system under lightning stroke and short circuit is studied. Secondly, the influence of instantaneous impulse current and lightning overvoltage on the secondary equipment in the fusion station and the tolerance and protection measures of the secondary equipment are analyzed. At last, the actual values and limits of the safety parameters of the three-in-one integrated grounding system are calculated by simulation based on CDEGS software, and relevant measures to improve the safety are put forward. The research shows that the integration construction of three stations grounding system can reduce GPR difference and improve the safety of three-in-one stations.
Detecting Hate Speech through Machine Learning

Hatred and abusive speeches are identified as huge crime that have been incrementing very recent years, and this has been not only in the specific interaction done face to face but preferably also in the online sharing of information. A considerable number of factors have been contributing to this. There has been a specific study that has well provided a kind of critical overview on the way of detecting such speeches within post or text has been highly evolved over the last few years. However, it has been observed that there are few studies that have been published in detecting hate speech automatically from the perspective of computer science. There is a great way or process with the support of which hate speech can be detected. It has been observed that both the automatic speech recognition and machine learning (ML) have been together complementing each other in the current past, and this has been because both the paradigms are very much deeply ingrained in each other. Therefore, this chapter aims to find out the relationship between hate speech detection and ML and find out the feasible ML algorithms to control hate speeches in social media. It has been observed that there is the implementation of a huge range of several methods of classifying the utilization of the embedding learning for computing all the distances which are semantic in between various parts of the speech which is properly considered to be a specific part of the “othering” narrative. It has also been observed that both the automatic recognition of speech and the ML have been hugely complementing each other in the current past, and this has been just because of the fact that both the paradigms are very much deeply ingrained in each other.
8th International School and Conference “Saint-Petersburg OPEN 2021” on Optoelectronics, Photonics, Engineering and Nanostructures

M V Maximov 1,2 , E I Moiseev 2,1 , N V Kryzhanovskaya 2,1 , A E Zhukov 2,1 1 Alferov Federal State Budgetary Institution of Higher Education and Science Saint Petersburg National Research Academic University of the Russian Academy of Sciences 2 National Research University “Higher School of Economics” moiseev@spbau.com, aezhukov@hse.ru 8th International School and Conference “Saint-Petersburg OPEN 2021” on Optoelectronics, Photonics, Engineering and Nanostructures was held on May 25 - 28, 2021. The Organizers of the conference are the National Research University “Higher School of Economics” and Alferov Saint Petersburg National Research Academic University of the Russian Academy of Sciences. More than 300 participants from Russia, CIS countries, Europe and America took part in the conference. The conference consisted of poster reports presented by the young participants (students, PhD students, and young researchers) and topical lectures by invited speakers. Due to restrictions imposed by the city authorities on holding mass events due to the threat of the spread of the COVID-19 infection, this year’s conference was held in a hybrid format at the HSE University (Saint-Petersburg, Russia). Most of the participants were present in person, while the rest could listen to reports and ask their questions on-line. Some of the speakers also made their presentations in a distant format. All performances were recorded and are available for viewing at the link https://www.youtube.com/watch?v=pRoRU6T-uM8&amp;t=5s. Posters and video reports of the participants were posted on the conference website https://spb.hse.ru/spbopen/. List of Committees, Conference Photograph are available in this pdf.
Meta-Analysis Methods for Health and Experimental Studies

Journal of the Royal Statistical Society: Series A (Statistics in Society)Early View BOOK REVIEW Meta-analysis methods for health and experimental studies , Khan, Shahjahan, 2020, 1st edition Springer Nature, 293 pages, Price 67,59 € (hardcopy) 53,49 € (eBook), ISBN 978-981-15-5032-4 A.K. Md. Ehsanes Saleh, A.K. Md. Ehsanes Saleh esaleh@math.carleton.ca School of Mathematics and Statistics, Carleton University, Ottawa, CanadaSearch for more papers by this author A.K. Md. Ehsanes Saleh, A.K. Md. Ehsanes Saleh esaleh@math.carleton.ca School of Mathematics and Statistics, Carleton University, Ottawa, CanadaSearch for more papers by this author First published: 16 December 2021 https://doi.org/10.1111/rssa.12785Read 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 onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Early ViewOnline Version of Record before inclusion in an issue RelatedInformation
Experimental Programming of Genetic Algorithms for the “Casse-Tête” Problem

The Casse-tête board puzzle consists of an n×n grid covered with n^2 tokens. m&amp;lt;n^2 tokens are deleted from the grid so that each row and column of the grid contains an even number of remaining tokens. The size of the search space is exponential. This study used a genetic algorithm (GA) to design and implement solutions for the board puzzle. The chromosome representation is a matrix of binary permutations. Variants for two crossover operators and two mutation operators were presented. The study experimented with and compared four possible operator combinations. Additionally, it compared GA and simulated annealing (SA)-based solutions, finding a 100% success rate (SR) for both. However, the GA-based model was more effective in solving larger instances of the puzzle than the SA-based model. The GA-based model was found to be considerably more efficient than the SA-based model when measured by the number of fitness function evaluations (FEs). The Wilcoxon signed-rank test confirms a significant difference among FEs in the two models (p=0.038).
An analysis of Spanish writing/translation errors due to excessive equation of correspondence between vocabulary/forms.

This paper analyses the errors due to Korean interference when writing/translating into Spanish. We claim that, when learners once input into memory a Spanish form “α” that most preferentially corresponds to a Korean form “A,” they tend to equate this correspondence as ‘A = α’ and apply it to cases where such correspondence should not be used. To find out how many learners make this type of error we conducted an experiment with 42 students. In the experiment, we divided the sentences into two groups. The sentences that can produce an appropriate result were placed in group A if we use the correspondence ‘A → α’, whereas those that can produce an inappropriate result were placed in group B if we do the same. Our analysis showed that the most common error in group B is to reuse the correspondence used in group A. Therefore, learners need to avoid an “excessive equation” to reduce errors. Finally, for each sentence, we suggested ways to reduce or avoid errors.
Vehicle Re-Identification and Tracking Based on Video Segmentation

Traffic object perception based on cameras is one of the foundations of Intelligent Transportation Systems. In traditional computer vision field, we usually take object detection method to detect and track the vehicle objects using bounding boxes with fixed shape, and some efficient methods based on this such as DeepSORT are used for perception. However, under the situation of dense traffic, vehicles could block each other in the viewpoint of the roadside camera, which severely reduce the accuracy of detection and tracking. Aiming to solve this, we propose our detection and tracking method based on partial feature re-identification and mask segmentation. First we apply segmentation method to separate the pixel-level image of each vehicle, then we use the especially trained CNN-based feature extractor to get the key information from the misshapen images, and finally utilize the masks and the features to track the vehicles. We test our method on CityFlow dataset and prove the validity of our method by visible result. We finally discuss the weakness of our framework and putting forward the future improvement direction of the algorithm.
Duty to protect and responsibility to respect: data privacy violations in pandemic times

How far can State and businesses ‘play’ with personal data, claiming to protect the right to health in pandemic times? This question leeds to the discussion of the possible damage caused by profiling and contact tracing techniques regarding personality rights in relations between ICT companies and States’. By analysing the way European and Inter-American bodies are tackling data protection rules currently in force, the text analyses the consent as a problematic issue, considering both the opt-in and opt-out model are not enough to protect those rights, especially in pandemic times. Although contact tracing might be used in favour of Public Health policies, it may also result in the violation of human rights. Applying the inductive method, this paper proposes a reflection about online behavioural tracking and profiling practices, explaining the efects of personal data mass gathering and the complex relations between businesses activities and human rights. The main conclusion is that all individuals have the same right to privacy, equality and freedom of choice. Thus, States should provide clear and objective rules to be followed by ICT companies, in accordance with international rules, ensuring individual’s protection and holding data processors accountable for personal data processing.
Books

Bert Gunter reviews A History of Data Visualization &amp; Graphic Communication.
Creative Destruction in School Education during COVID-19

Lockdown measures and school closures due to the coronavirus forced governments, schools, and teachers to rapidly find new ways to ensure learning continuity. Based on Joseph Schumpeter’s concept of creative destruction, we argue that COVID-19 was a powerful and accelerating force for innovation in schools. Through the analysis of in-depth interviews with school principals in Argentina, we explore and discuss the consequences of COVID-19 on pedagogy and school institutions, particularly the relationship between socioeconomic conditions and possibilities of innovation in education. Our findings suggest that in an eight-month period, private, high socioeconomic composition schools, which hold large amounts of financial resources and broad decision-making margins, developed distinct organizational methodologies that disrupted schools’ time, space, and order. These methodologies, in turn, allowed these institutions to thoroughly sustain the educational process of their students and to provide more efficient learning opportunities. We suggest possibilities of incorporation of these experiences in the future when schools reopen.
Training of Primary School Specialists Taking Into Account Up-to-Date Opportunities for Self-Improvement

The purpose of the research is to analyze the training of primary school specialists taking into account the up-to-date opportunities for self-improvement at the stage of university training and at the early stage of professional activity (the first 3-5 years after starting work at school). In order to obtain empirical data, a diversified diagnostic model has been developed, within which a questionnaire has been conducted and a method of presenting a portfolio of professional self-improvement has been applied. The research based on the tactics of self-reflection of graduates has showed a high level of formation of professional self￾improvement, which is partly due to the selection criteria of respondents. Comparison of the results with the data of the studied group of respondents – primary school teachers with teaching experience ≥5 years allowed assessing the dynamics of professional self-improvement at the stages of pre-service and in-service training, as well as identifying promising areas of professional self-improvement, which should be emphasized during the university training of future primary school teachers.
Emotion classification and language characteristics analysis of "fans community" based on NLP

As abuse and malicious rumor often occur in the " fans community ", which has an extremely bad impact on the society, we need to study the emotional tendency of the comment language of the " fans community " in the network, so as to identify the "loyal fans" and "black fans" and explore the language characteristics of the two types of fans. In this paper, more than 50,000 comments were extracted from common Chinese websites, and some data were pre-processed and manually annotated to construct a Chinese "fans community" comment dataset. The three supervised algorithms and one unsupervised algorithm for" fans community ". Emotional dictionary method are used to classify the " fans community " comment information. Then it is analyzed such as the content of the two types of fans comments in terms of sentences, word count, words, and so on. The experimental results show that all the methods adopted in this paper can effectively classify the comments of "loyal fans" and "black fans" by emotion dichotomy. In terms of language characteristics, the comments of "loyal fans" are characterized by multiple nouns, long sentences and regular comment time. "Black fans" comments are often verbs, short sentences and random comments.
The place of linguistics in modern sci-fi and fantasy studies

The article analyzes the most significant foreign studies of sci-fi and fantasy in order to define the place of linguistics in this sphere of research, to highlight relevant linguistic problems that require further research. Two main development directions of linguistic studies are emphasized, and the necessity of the further specifically linguistic study of certain problems is established.
Photometric Ligature Extraction Technique for Urdu Optical Character Recognition

Urdu Optical Character Recognition (OCR) based on character level recognition (analytical approach) is less popular as compared to ligature level recognition (holistic approach) due to its added complexity, characters and strokes overlapping. This paper presents a holistic approach Urdu ligature extraction technique. The proposed Photometric Ligature Extraction (PLE) technique is independent of font size and column layout and is capable to handle non-overlapping and all inter and intra overlapping ligatures. It uses a customized photometric filter along with the application of X-shearing and padding with connected component analysis, to extract complete ligatures instead of extracting primary and secondary ligatures separately. A total of ~ 2,67,800 ligatures were extracted from scanned Urdu Nastaliq printed text images with an accuracy of 99.4%. Thus, the proposed framework outperforms the existing Urdu Nastaliq text extraction and segmentation algorithms. The proposed PLE framework can also be applied to other languages using the Nastaliq script style, languages such as Arabic, Persian, Pashto, and Sindhi.