Reviewerly/exHarmony huggingface dataset:
Hybrid Feature Extraction Based Ensemble Classification Model to Diagnose Oral Carcinoma Using Histopathological Images

Detection and classification of cancerous tissue from histopathologic images is quite a challenging task for pathologists and computer assisted medical diagnosis systems because of the complexity of the histopathology image. For a good diagnostic system, feature extraction from the medical images plays a crucial role for better classification of images. Using inappropriate or redundant features leads to poor classification results because classification algorithm learns a lot of unimportant information from the images. We propose hybrid feature extractor using different feature extraction algorithms that can extract various types of features from histopathological image. For this study, feature fused Convolution Neural Network, Gray Level Cooccurrence Matrix, and Local Binary Pattern algorithms are used. The texture and deep features obtained from these methods are used as input vector to classifiers: Support Vector Machine, KNearest Neighbor, Naïve Bayes and Boosted Tree. Prediction results of these classifiers are combined using soft majority voting algorithm to predict final output. Proposed method achieved an accuracy of 98.71%, which is quite high as compared to previous similar research works. Proposed method was capable of identifying most of cancerous histopathology images. The combination of deep and textural features can be potentially used for creating computer assisted medical imaging diagnosis system that can detect cancer from histopathology images timely and accurately.
Replica Scheduling Strategy for Streaming Data Mining

In a distributed storage and computing framework, traditional streaming data mining techniques are inefficient when processing massive amounts of data.In this paper, we take the copy in cloud storage as an allocatable resource for scheduling and propose a RepRM strategy to improve the efficiency of data mining and analysis.The key idea of this work is to take the data copy as the resource to be allocated, and use the backward inference method of dynamic programming to solve the data copy ratio, the optimal number of copies is obtained.Experiments and observations have proved that compared with the traditional scheduling method of Hadoop, after adopting the RepRM strategy scheduling, the memory resources of the homogeneous cluster are saved by about 40-50% during parallel mining of streaming data, and the throughput rate is increased by 20% to 30%.
A Statistical Modeling Framework for DCT Coefficients of Tampered JPEG Images and Forgery Localization

Various manipulations on JPEG images introduce single and multiple compression artifacts for forged and unmodified areas respectively. Based on the statistical analysis of JPEG compression cycle and on the finite mixture paradigm, we propose in this paper a modeling framework for AC DCT coefficients of such tampered JPEG images. Its accuracy is numerically assessed using the Kullback-Leibler divergence on the basis of a tampered JPEG image dataset built from six well-known uncompressed color image databases. To illustrate the framework utility, an application in image forgery localization is proposed. By formulating the localization as a clustering problem, we use the plug-in Bayes rule combined with a simple EM algorithm to distinguish between forged and unmodified areas. Numerous experiments show that, when the quality factor of final JPEG compression is high enough, the proposed modeling framework yields higher localization performances in terms of <i>F</i><sub>1</sub>-score than prior art regardless of divers local manipulations.
Periodontal Research Wars: Navigating Through Minefield of Statistical Jargon

Statistical analysis is considered to be the backbone of research and however challenging it is to a clinician, it playsa crucial part for a researcher to comprehend the various presumptions underlying the statistical methods. In thefield of periodontology, statistical analysis is routinely used for management and interpretation of data. Yet, manyperiodontists find it difficult to understand the various statistical methods used in periodontal researches. Thus,this paper aims to cover the basictenetsof statistical analysisin a simplified manner with the help of flowcharts,specially emphasising on understanding few crucial points beforechoosing any statistical test. Later section of thearticle takes an application-based approach by incorporating the already illustratedflowcharts and crucial points.
THE INTERACTION BETWEEN SCHOOL AND UNIVERSITY: AN INFRASTRUCTURE PROJECT

The article presents the target, content and technological features of the infrastructure project, in the implementation of which the capital’s schools, pedagogical university, organizations of additional education of children are involved. The project is aimed at the development and introduction into the educational process of educational and methodologi- cal support for the development of the culture of research and project activities of schoolchildren as a meta-subject result in the conditions of network interaction of educational organizations of general and higher education.
The Scholarly Communications Cookbook. Brianna Buljung and Emily Bongiovanni, eds. Chicago, IL: Association of College and Research Libraries, a division of the American Library Association, 2021. 358p. Softcover, $88.00 ($79.20 ALA members) (ISBN: 978-0838938478).

The Scholarly Communications Cookbook , edited by Brianna Buljung and Emily Bongiovanni, offers a wide range of successful scholarly communications programs and projects that can serve as inspiration for librarians seeking to expand scholarly communications services at their institutions. A broad scope of scholarly communications topics is represented, including open access (OA) publishing services, open educational resources (OER) initiatives, research support tools, campus collaborations, and teaching and learning opportunities.
Science Literacy-Based E-Module Development in Elementary Students

In this study, the development of an E-Module based on science literacy was carried out on the ecosystem theme which was used to improve science literacy for fifth grade elementary school students.The results showed that the validation process by the media expert validator obtained an average of 4.76 with the "Very Good" category, the percentage of eligibility was 95% which was categorized as "Very Eligible", the validation process by the material expert validator obtained an average value of 4.71 "Very Good" categories with a percentage of 94% categorized as "Very Eligible".Practicality tests by education practitioners obtained a practicality percentage 95% and were included in the "Very Practical" category.The results of student responses obtained a percentage 96% and were included in the "Very Practical" category.Based on the results of the effectiveness test of the E-Module, it can be seen that after using the E-Module, the average score of students increased from the initial average before using it, namely 61.25 with the "Enough" category and the completeness criteria "Not Complete" to 87.18 with "Very Good" category and completeness criteria "Complete".
Where is My Mind?

Abstract The research field of AI is concerned with devising theories, methods, and workflows for producing software artifacts which behave as intelligent subjects. Evidently, intelligence, as the property of an agent, is not of necessity inherited from the methods used to construct it: that a car has been assembled by robots does not make it a robot. Unfortunately, even this obvious distinction can sometimes be erased in some prominent published work. To wit: the statement, “an agent that performs sufficiently well on a sufficiently wide range of tasks is classified as intelligent” was recently published by DeepMind [273] to give context to a paper claiming to have developed “the first deep RL agent that outperforms the standard human benchmark on all 57 Atari games” [14]. This invites the inference that the range of the tasks (57 games) that have been achieved warrants calling the advertised agent ‘intelligent’. However, careful reading of the paper reveals that the authors have in fact developed 57 different agents. Granted, this was achieved using the same development method and system architecture, but 57 agents were nonetheless trained, rather than the claimed single agent. Here is a prime example of distilled confusion: a property (applicability to 57 tasks) of one construction method (instantiating the Agent57 system architecture) has just been ‘magically’ transferred to some 57 artifacts produced by the method.
Nigeria’s Socio-Economic Factors and Ekiti State’s Youth Involvement in Agriculture

Out of many other options to increase sustainable production of foods to feed its teeming population, Nigerian academics now focus on the possibility of motivating the youths into action in a labour intensive drive; finding reasons why Nigerian youths are not taking to farming. It is well known that a lot of young college and university graduates left the shores of Nigeria only to be engaged by strangers in cultivating plantations in foreign lands as a mean of livelihood. The shame of their discovery and the inability to raise adequate funds with which they would return home eventually keep them in long servitude abroad. Moreover, a lot of studies have ensued in regard of this, but none has been done or reported on Ekiti youths. This study fills the gap. A sample of 300 respondents from the population was drawn using multistage sampling method. Five focal questions were raised in the study and two hypotheses were generated and tested (at 0.05 level of significance) using the chi-square inferential statistical method. Data were collected using a well-structured questionnaire; the research design can be best described as a descriptive survey. Study unveiled that what youths really need most in Ekiti to encourage them in taking on agriculture include finance, awareness, training, fertile land, loan facility, power supply, loan facility, power supply, improved seedlings, fertilizer/agrochemicals availability, and machinery among others.
INTERACTIVITY OF THE LEARNING PROCESS IN THE CONTEXT OF VIRTUALIZATION: NEW REQUIREMENTS FOR SOCIAL AND HUMANITARIAN EDUCATION

Digital technologies have increased the opportunities for vocational education, its relevance, openness and accessibility, made the educational process more dynamic, interesting and flexible. However, the educational process does not only require appropriate equipment and technology, but also a sociocultural environment appropriate to the time, the basis of which is interactivity. Interactivity begins to perform the functions of a new educational environment under the conditions of virtualization and only under the condition of interactivity of all forms of classes – lectures, seminars, independent work, etc. – efficiency and quality of learning can be achieved. The best practices of modern educational environment should combine the cultural background of live communication and digital communication space.
A Case Study of Talent Training: Based on the Cooperation Between University and Enterprise

Talent training is considered one of the most important in this scenario that is beneficial for enhancing the competitive advantage of students and teaching staff.Good cooperation between universities and enterprises can increase learning and thinking ability to face increasingly severe employment pressure and social demand.This study selected the talent training model from the school of Business Administration of Guangzhou Institute of Science and Technology as the primary sample.This training model is also called "Innovation Class" that is designed to train professional headhunters under the new university-enterprise cooperation policy.We took the contrast method, questionnaire survey, and data analysis to explore a suitable way for private undergraduate universities to build a talent training mode and cultivate classified innovation as well as application.
PEDAGOGICAL CONDITIONS FOR THE USE OF DIGITALIZATION TOOLS IN DISTANCE LEARNING

The article discusses the ways of using digitalization and communication tools in the field of education. This process of intellectualization of the activities of the teacher and the learner develops on the basis of the implementation of the didactic capabilities of information and communication technologies.
Ext4

Abstract The Ext4 file system is often used by Android cell phones and by Linux distributions. As a mobile forensic expert, it is necessary to understand the structures of this file system to recover data, verify tool results, and detect anti-forensics techniques that may be present in the file system. In this chapter, we will have a deep dive into topics important for an investigation. Many digital forensic tools do not recover much from the Ext4 file system [52], and therefore we show some of the most useful Ext4 recovery techniques proposed by current research. The Ext4 file system is often used by Android1 operating systems, and also by Linux desktop distributions [14], and this file system is open source. The Ext4 file system replaces the Ext2 and Ext3, but it is mostly backwards compatible. Carrier described Ext2 and Ext3 in his File System forensic analysis book [10], which includes information also relevant for Ext4. Fairbanks describes the Ext4 file system at a low level and from a Digital Forensics perspective. This chapter will describe file system information important for mobile forensic investigators and other digital forensic experts.
Knowledge Map Construction and Visualization with Weight

Knowledge map construction and visualization of characters and related information in novel sand films can help readers or audiences understand the content of related works more accurately and quickly.Taking the novel "In the Name of the People" as an example, the occurrence frequency of main characters and co-occurrence frequency between characters are introduced into the knowledge map in the form of weights to form the knowledge map of characters and relationships with weight, and the Web programming technology of JavaScript is used to visualize it.It is compared with the knowledge map constructed by graph database Neo4j.Compared with the knowledge map constructed by Neo4j, the weighted knowledge map of people and relationships can display the importance with weight of characters and the closeness of the connection between characters more intuitively.
A FOOTPRINT ON THE GROUND. ALEXEY FEDOROVICH TRESHNIKOV

The research work is devoted to the study of the life and scientific path of Alexei Fedorovich Treshnikov. Practical work has been carried out aimed at the formation of the civic position of schoolchildren and the upbringing of love for their small homeland.
Adaptation of the procedure for designing local learning systems to the requirements of system engineering

The article clarifies the requirements of system engineering for the procedure of designing local learning systems. On the basis of comparative analysis of these requirements with the procedure of designing the learning process generally accepted in pedagogy, the essence of the inconsistencies of individual pedagogical design procedures with the requirements of system engineering is revealed. The causes of the identified inconsistencies and approaches to their elimination are analyzed. The difference in the approaches of system engineering (pragmatic approach) and pedagogy (research approach) to the definition of design goals is considered as the main cause of the identified inconsistencies. The prospects of developing a practical (pragmatic) variant of pedagogical design are substantiated and a variant of the V–model of the system engineering method is presented, which is focused on the development of local learning systems.
Analysis of Bangla Keyboard Layouts Based on Keystroke Dynamics

Rohan, Shadman Roy, Koushik Saha, Pritom Kumar Hossain, Sazzad Rahman, Fuad Mohammed, NabeelKeyboards are the primary devices for interaction with computer platforms and have been a central topic in HCI research for decades. The study of their layout design is important in deciding their efficiency, practicality and adoption. Multiple keyboard layouts have been developed for Bangla without any rigorous study for their comparison. In this paper, we take a quantitative data-driven approach to compare their efficiency. Our evaluation strategy is based on the key-pair stroke timing with data collected from standard QWERTY English keyboards. Our experiments conclude that the Bijoy keyboard layout is the most efficient design for Bangla among the four layouts studied. This quantitative approach can lay the groundwork for further study of these layouts based on other criteria.
A Highly Customizable Information Visualization Framework

The human brain can quickly become overwhelmed by the amounts of data computers can process. Consequently, data abstraction is necessary for a user to grasp information and identify valuable patterns. Data is usually abstracted in a pictorial or graphical format. Nowadays, users demand more personalization from the systems they use. This work proposes a user-centered framework that aims to ease creating visualizations for the developers of a platform while offering the end-user a highly customizable experience. The conceptualized solution was prototyped and tested to ensure the information about the data is transmitted to the user in a quick and effective manner. The results of a user study showed that users are pleased with the usability of the prototype and prove that they desire control over the configuration of their visualizations. This work not only confirmed the usefulness of previously explored personalization options for visual representations, but also explored promising new personalization options.
The prospect of gaze manipulation technology in decision-making research

操纵效果, 并分析和讨论了不同操纵类别的优缺点。在实验设计中考虑决策者策略及偏 好的差异, 结合计算建模等方法进一步丰富操纵指标和分析方法, 并将该方法的优势拓展到其它领域是眼动 操纵研究未来的重要方向。
Interactive Latent Knowledge Selection for E-Commerce Product Copywriting Generation

As the multi-modal e-commerce is thriving, high-quality advertising product copywriting has gain more attentions, which plays a crucial role in the e-commerce recommender, advertising and even search platforms.The advertising product copywriting is able to enhance the user experience by highlighting the product's characteristics with textual descriptions and thus to improve the likelihood of user click and purchase.Automatically generating product copywriting has attracted noticeable interests from both academic and industrial communities, where existing solutions merely make use of a product's title and attribute information to generate its corresponding description.However, in addition to the product title and attributes, we observe that there are various auxiliary descriptions created by the shoppers or marketers in the ecommerce platforms (namely human knowledge), which contains valuable information for product copywriting generation, yet always accompanying lots of noises.In this work, we propose a novel solution to automatically generating product copywriting that involves all the title, attributes and denoised auxiliary knowledge.To be specific, we design an end-to-end generation framework equipped with two variational autoencoders that works interactively to select informative human knowledge and generate diverse copywriting.Experiments on real-world e-commerce product copywriting datasets demonstrate that our proposed method outperforms various baselines with regard to both automatic and human evaluation metrics.
DAN-NucNet++: A Bottom-Up Framework Using Dual Attention Network for Simultaneous Nuclei Segmentation and Classification in Digital Histology Images

Simultaneous nuclei segmentation and classification in digital histology play a fundamental role in diagnosing cancer. The segmentation and classification of nuclei in digital histology is challenging due to the higher morphological variability, staining variability, variability across the tissue, rough clinical conditions, and class imbalance. Recent deep learning methods have shown improved performance. However, these methods still have a considerable improvement gap, especially in complex situations. In our previous network, DANNucNet, we have resolved some of these issues using both channel and spatial attention mechanisms for semantic segmentation. In this work, we utilize our previous network to develop a mechanism, for instance, segmentation and classification, using a bottom-up approach. We propose a dual spatial-channel attention-based three head model, which produces semantic segmentation, edge maps, and classification maps. Then, like bottom-up approaches, we use edge maps and semantic segmentation to apply controlled watersheds to produce instance segmentation maps. Then using the instance segmentation maps, we further clean the classification maps using pixel grouping. The proposed method is tested on the recently released largest available dataset, PanNuke. We demonstrate a significant performance improvement in semantic segmentation, thus producing high-quality instance segmentation and nuclei classification compared to the state-of-the-art. We have achieved a 0.841 Dice score for semantic segmentation, 0.713 bPQ scores for instance segmentation, and 0.633 mPQ for nuclei classification. Our proposed framework is generalized across 19 different types of tissues. Furthermore, the framework is less complex compared to the state-of-the-art. The performance improvement and robustness of the proposed method will have positive implications on procedures requiring nuclei segmentation and classification.
The COVID-19 Hate Crime Act: Anti-Chinese Sentiment and Xenophobia in Times of Austerity

On March 16, 2021, the fatal shootings that took place at three massage parlors in Atlanta, Georgia, targeting women of Asian descent took away 8 innocent lives.However, this is only one of the tragic incidents that caused racial animus occurred during the pandemic.An upsurge of anti-Asian sentiment was detected in the early days of the pandemic, leading to a bipartisan effort to fight bias-driven incidents against Asian Americans led to Congress's passage of the Covid-19 Hate Crimes Act.This paper conducts a descriptive study to examine the efficacy of the COVID-19 Hate Crimes Act through literature review, mainly focusing on three themes: historical, political, and social.The paper first evaluates the design of the bill, then analyzes and explains factors that hinder its effectiveness, and lastly, proposes alternative solutions.The paper finds that the COVID-19 Hate Crimes Act serves more of a symbolic purpose, a needed wake-up call, but inadequate to bring the progress Asian communities need and to temper the deeply rooted xenophobia.
АНАЛИЗ РОССИЙСКОЙ СИСТЕМЫ ВЫСШЕГО ОБРАЗОВАНИЯ И ВЫЯВЛЕНИЕ ИСТОЧНИКОВ КОНФЛИКТНЫХ СИТУАЦИЙ В ВЫСШЕМ УЧЕБНОМ ЗАВЕДЕНИИ

The article, based on the analysis of the higher education system, identifies the sources of production contradictions in a higher educational institution and determines the need to develop scientific tools for studying, as well as practical solutions to labor conflicts that entail destructive consequences. A comprehensive study of the educational process in order to ensure a comfortable socio-psychological component of the professional activities of teachers, which will positively affect the quality of educational services and the image of the educational institution, should become the basis for preventive protection of university employees from sources of conflict situations