Reviewerly/exHarmony huggingface dataset:
Violence Recognition from Videos Using Deep Learning

Violence recognition is a process of recognizing violent activities in public places through video surveillance. Violence recognition can be used to monitor violence in public places through video surveillance. In this paper, CNN algorithm is implemented with MobileNetV2 architecture and OpenCV for violence recognition. In this system, we use various real-life-based videos to train our system in which half of the dataset contains violence videos and another half contains safe videos. The proposed model achieves the accuracy of 94%.
Fine‐Grained Scene Graph Generation with Overlap Region and Geometrical Center

Abstract Scene graph generation refers to the task of identifying the objects and specifically the relationships between the objects from an image. Existing scene graph generation methods generally use the bounding boxes region features of objects to identify the relationships between objects. However, we feel that the overlap region features of two objects may play an important role in fine‐grained relationship identification. In fact, some fine‐grained relationships can only be obtained from the overlap region features of two objects. Therefore, we propose the Multi‐Branch Feature Combination (MFC) module and Overlap Region Transformer (ORT) module to comprehensively obtain the visual features contained in the overlap regions of two objects. Concretely, the MFC module uses deconvolution and multi‐branch dilation convolution to obtain high‐pixels and multi‐receptive field features in the overlap regions. The ORT module uses the vision transformer to obtain the self‐attention of the overlap regions. The joint use of these two modules achieves the mutual complementation of local connectivity properties of convolution and the global connectivity properties of attention. We also design a Geometrical Center Augmented (GCA) module to obtain the relative position information of the geometric centers between two objects, to prevent the problem that only relying on the scale of the overlap region cannot accurately capture the relationship between two objects. Experiments show that our model ORGC (Overlap Region and Geometrical Center), the combination of the MFC module, the ORT module, and the GCA module, can enhance the performance of fine‐grained relation identification. On the Visual Genome dataset, our model outperforms the current state‐of‐the‐art model by 4.4% on the R@50 evaluation metric, reaching a state‐of‐the‐art result of 33.88.
HOW IS THE QUALITY OF READING TEST ITEMS ON ENGLISH SUBJECT?

The objective of the study is to ascertain the quality of the reading test items on English subject for the eighth students at SMPN 12 Tasikmalaya. Those items were analyzed based on difficulty level items, discrimination power, and distractor effectivity. This study employed descriptive quantitative. It is implemented to describe the quality of reading test item of eighth students of SMPN 12 Tasikmalaya. Whereas, quantitative data used as the data or information in the form of numerical data and analyzed it by using Item and Test Analysis (ITEMAN) program 3.0 version. The researchers had already conducted the study on reading in previous study, so in collecting the data, the researcher used the documentation. It used to know the quality of reading test items that had been made by the first researcher. The results showed that: 1) based on difficulty level of items indicated 14 (23%) items in easy, 32 (53%) items in medium, and 14 (23%) items in hard. Dealing to discrimination power of items, it showed that 51 (85%) items in very good, 5 (8%) in good, 0 (0%) in enough, and 4 (7%) in poor, must be discarded. Meanwhile, the distractor effectivity on reading test items on English subject of eighth students of SMPN 12 Tasikmalaya were: 44 (73%) items in function, 12 (420%) items in enough, 2 (7%) items in unfunctional, and 0 (0%) items in poor. Overall, the quality of reading test which had been made by the first researcher in previous study was in good quality.
The Arts and Play as Educational Media in the Digital Age, Robert Albrecht and Carmine Tabone (2020)

Review of: The Arts and Play as Educational Media in the Digital Age , Robert Albrecht and Carmine Tabone (2020) New York: Peter Lang, 168 pp., ISBN 978-1-43315-425-6, h/bk, $64.98 ISBN 978-1-43315-426-3, p/bk, $20.58 ISBN 978-1-43315-427-0, e-book, $38.90
Research on the application of holographic projection technology in apparel display

We provide customers with the best shopping experience, save cost of clothing display, make the whole process of clothing design more visualized, three-dimensional and interactive, and then improve the efficiency of brand culture information transmission, so that the concept of fashion design can be fully reflected. This paper starts from the concept and basic principle of 3D hologram technology, and explores the application of virtual reality technology in apparel display from three aspects: fashion show, virtual fitting, and offline attraction, in order to promote the deeper application of holographic projection technology in the apparel industry.
Cyberbullying detection through deep learning: A case study of Turkish celebrities on Twitter

One of the ways that celebs maintain their fame in the modern era is by posting updates and photos to social media platforms like Twitter, Instagram, and Facebook. Comments left on their posts, however, expose them to cyberbullying. Cyberbullying, as a form of electronic device-based harassment, negatively impacts the lives of individuals. Thirty famous people from the fields of acting, art, music, politics, sports, and writing were chosen for this research. These notable figures include the top five Twitter followers of Turkey in each demographic. Between December 2019 and December 2020, comment responses for each celebrity were collated. Using the Deep Learning model, we were able to detect abuse content with an accuracy of 89%. Additionally, the percentage of celebrities exposed to cyberbullying by group was presented.
The Art of the Exploit: Gender Hacking and Political Agency

This article considers the idea of gender hacking, particularly as it circulates in Paul B. Preciado’s Testo Junkie, and places this in the context of wider discourses of both bio- and computer hacking. Of particular interest is how a hacking paradigm has come to inform twenty-first-century theories of activist intervention, and the implications of this for contemporary conceptions of political agency. Drawing out the parallels between conceptualizations of hacking and transgression, the article considers both the possibilities and the potential limitations of thinking about sociopolitical changemaking in these terms. Ultimately, it uses theories of transgression to propose a rethinking of the distinction between engineering and hacking, with a view to negotiating the conflict between micropolitical hormonal intervention and ambitions toward re-engineering biotechnical hegemony in gender-hacking projects.
Foreword

Cyber security breaches continue to significantly threaten governments, businesses and individuals worldwide. The demand for cyber security professionals has increased significantly in recent years around the world and is expected to continue to grow, and this trend has created shortages in labour markets in several countries. The first step in addressing skills shortage in the cyber security sector is to understand the supply and demand dynamics of cyber security skills. This information can be used by governments and organisations to identify their vulnerabilities and determine where additional resources are needed. By analysing job postings, trends in demand for cyber security professionals and the skills for creating a secure organisational environment can be identified. Meanwhile, studying the provision of cyber security education and training programmes provides insights into how the cyber security workforce is being developed and the potential misalignment between demand and supply.
Key insights for building a skilled cyber security workforce

This chapter provides an overview of the report’s objectives and rationale and summarises the main takeaways. It discusses the results from the analyses of the demand for cyber security professionals in Australia, Canada, New Zealand, the United Kingdom and the United States. It also summarises the main findings from the analysis of the landscape of cyber security education and training programmes in England (the United Kingdom). It concludes with actionable policy pointers.
Bruce Caron is Keeping Tabs on AI

Like the rest of you, I’ve been deluged with opinions and advice about recent advances in AI. So, I hopped into the AI mosh-pit. Last fall, I grabbed an account on DALL-E and spun up intricate artwork in my spare time. I jumped on Chat GPT 3.5 when it arrived, and this week, on GPT-4. I have an open tab that takes me to my account with Openai.
Research on multi-scenario crowd density monitoring and management system based on Beidou technology

In recent years, the state has vigorously promoted the development of tourism and service industries. At the same time, public security incidents have occurred frequently due to excessive crowd density. Therefore, it is necessary to establish a multi-scenario crowd density monitoring and management system. In this regard, this paper proposes a multi-scenario crowd density monitoring and management system based on Beidou technology, so that managers can formulate scientific crowd control measures. The system consists of three parts: intelligent car, server and user. The smart car moves in a certain area according to the specified trajectory or autonomous navigation. At the collection point, the OpenMV module carried on the car uses the Haar operator to realize face detection. The face detection works by using the Haar Cascade feature detector on the image. Haar Cascades runs very fast, and can be better applied to face detection in the case of people walking. It counts the number of detected faces, and the acquired number is transmitted to the motherboard and the short message sent by the GPS Beidou dual-mode positioning module. The text is sent to the server. The server side processes the number of people and location information received from the trolley. In special circumstances, the trolley can be remotely controlled through the WFI module, which is convenient for viewing at the place where the accident occurred. The client performs system settings on the server to obtain the required information. This system is based on Beidou technology, which helps decision makers to manage the flow of people to a great extent.
Nominal Sets in Agda - A Fresh and Immature Mechanization

In this paper we present our current development on a new formalization of nominal sets in Agda.Our first motivation in having another formalization was to understand better nominal sets and to have a playground for testing type systems based on nominal logic.Not surprisingly, we have independently built up the same hierarchy of types leading to nominal sets.We diverge from other formalizations in how to conceive finite permutations: in our formalization a finite permutation is a permutation (i.e. a bijection) whose domain is finite.Finite permutations have different representations, for instance as compositions of transpositions (the predominant in other formalizations) or compositions of disjoint cycles.We prove that these representations are equivalent and use them to normalize (up to composition order of independent transpositions) compositions of transpositions.
Demonstration and Comparison of Different Entanglement Fabrication Approaches

Quantum entanglement is the most representative feature of quantum mechanics to classical mechanics. It is the delocalization, non-classical strong correlation among multiple quantum system. It has been developed for nearly one hundred years and a lot of methods of production and applications have been proposed. Aiming at the generation mode of quantum entanglement, this study presents two general preparation methods of quantum entanglement sources, including spontaneous parametric down-conversion (SPDC) and the preparation of quantum entanglement sources based on the four-wave mixing (FWM) effect. The principle, advantages and disadvantages of quantum entanglement sources are analyzed respectively. Finally, the research and application direction of the preparation method of quantum entanglement source are prospected. With the ability of preparation of quantum entanglement source, the application of quantum entanglement developed quickly, (e.g., quantum teleportation, entanglement swapping, quantum key distribution and quantum dense coding in the area of communication), and other area such as quantum computer, quantum imaging, quantum ranging and quantum clock synchronization. These results shed light on guiding further exploration of entanglement fabrication.
Image Super-Resolution Via Gradient Guidance and Gnenrative Adversarial Network

In order to solve the problem that the existing image super-resolution reconstruction model generates poor visual quality and prone to structural distortion, a deep gradient guidance based on generative adversarial network is proposed. The generator introduces the gradient branch to transfer the features of the gradient image and fuses the gradient information with the image branch to prevent the image edge distorted. Referring to MSRB, ResNext and Inception, an improved multi-scale residual block is proposed and applied to the basic module of the image branch and gradient branch, which makes model easier to obtain multi-scale information. The discriminator uses WGAN-GP to improve the stability of network training. Compared with the perceptual-driven algorithms such as SRGAN, ESRGAN and NatSR, the proposed algorithm can effectively prevent structural distortion of the image and improve the quality of the generated image. The computational complexity of proposed model is 23.7GFLOPs, which is lower than ESRGAN and SPSR about 1/4 and 1/10.
Verification of a method for latent interest estimation based on user behavior analysis and POI attributes

Web advertising services for the Internet are growing rapidly. However, it is difficult to effectively recommend Web advertisements to latent buyers using the current mainstream Web ad recommendation method based on keyword matching with online search and browser history. This is because it is an explicit analysis using keywords that the user is already interested in. On the other hand, most of the advertisement recommendation methods using location information of mobile terminals are based on the distance to the actual store. Therefore, this research proposes and verifies a method to analyse latent user interest based on analysis of real-space user behavior considering point-of-interest (POI) attributes. We apply the method to Web advertisement recommendation on mobile terminals, and assume that the user’s interest targets are stores that exist in real space. Specifically, we use geotagged tweet data to extract the users’ movement activity range within a certain time period with reference to the store locations. The movement activity range serves as basis for POI attribute analysis using OpenStreetMap (OSM) data. Finally, the characteristics of the real-space movement activity history are extracted and used together with the POI attributes to train a XGBoost model. In previous research, we accumulated data, generated training models with various settings, and verified their prediction accuracy of users visiting a target stores. In this paper, we focus on verifying the effectiveness of the proposed advertising recommendation method by conducting a questionnaire survey of actual users.
Activities and Development of Open Universities in the States of European

The urgency of the research lies in the possibility of providing educational services even in the crisis conditions of modern times, caused by geopolitical problems and the spread of the global coronavirus pandemic. The activities of Open Universities in the states of the European Union are characterized by openness and the possibility of providing complex educational programs according to modern pedagogical practice. The importance of Open Universities’ activities is underpinned by the use of modern pedagogical methods, namely: distance education and interactive classes. The issue of applying the European education system of Open Universities is crucial to the possibility of improving the population’s general educational level and contributing to the enhancement of the population’s qualifications in EU states. The purpose of the academic paper is to study the principles of activity and aspects of the development of Open Universities in the states of the European Union. The objectives of the research are to analyse the functioning of Open Universities, define the educational program and outline the prospects for further development. The object of the research is the factors of activity and development of open universities in the European Union’s states based on modern digital technologies. By using the methods of scientific research, both exploratory and analytical ones, an assessment of the activities of Open Universities in European countries was carried out. The research methodology consists in the analysis of theoretical and methodological approaches to the Open University as an educational institution and conducting a study of the prospects for the development of Open Universities in the countries of the European Union. The results obtained can be used in practical training of students for their subsequent admission to higher educational institutions and improving the process of developing a complex of educational programs in Open Universities. The academic paper examines the principles and factors of the development of Open Universities in the countries of the European Union.
Fast seam carving for video with consideration of object misalignment suppression

In recent years, with the spread of devices with various screen sizes, the demand for resizing methods is increasing. Seam carving (SC) is one of the resizing methods. This method removes visually unimportant areas (hereinafter referred to as "seam") and resizes the image without losing its impression. SC for video images has the problem that the most impressive areas are shifted because the seams are different from frame to frame. There are previous methods to solve this problem, but they require a huge amount of processing time. The proposed method enables SC with reduced misalignment and processing time by area segmentation and seam reuse.
Prevention of Cyberbullying in Social Media: Perspective of Female Entrepreneurs in Bangladesh.

In recent years social media is a very popular platform for any kind of business. During the pandemic, it became even more trendy for small business owners who run businesses from home. Particularly in developing countries like Bangladesh where socially and culturally women face a lot of obstacles to doing business. The number of female entrepreneurs in Bangladesh is growing day by day as this is an opportunity for them to earn and support their families. Initially, they prefer social media for their business platform because there is no need for business premises, and it is easy to target a large number of customers in a short period of time. While the prospect of female entrepreneurship is bright for this country, they are encountering cyberbullying on social media by some ill-minded people. This paper aims to find out how female entrepreneurs in Bangladesh experience and can prevent cyberbullying on social media. This is exploratory research. Qualitative data were collected through an online semi-structured interview method by using open-ended questions. Data were analysed thematically based on different codes and themes by using NVivo 12 software. The result shows how female entrepreneurs get cyberbullied on social media in this country. It also recommends some preventive actions that female entrepreneurs can exercise to protect themselves from cyberbullying while operating their businesses on social media.
On Projectivity in Markov Logic Networks

Markov Logic Networks (MLNs) define a probability distribution on relational structures over varying domain sizes. Like most relational models, MLNs do not admit consistent marginal inference over varying domain sizes i.e. marginal probabilities depend on the domain size. Furthermore, MLNs learned on a fixed domain do not generalize to domains of different sizes. In recent works, connections have emerged between domain size dependence, lifted inference, and learning from a sub-sampled domain. The central idea of these works is the notion of projectivity. The probability distributions ascribed by projective models render the marginal probabilities of sub-structures independent of the domain cardinality. Hence, projective models admit efficient marginal inference. Furthermore, projective models potentially allow efficient and consistent parameter learning from sub-sampled domains. In this paper, we characterize the necessary and sufficient conditions for a two-variable MLN to be projective. We then isolate a special class of models, namely Relational Block Models (RBMs). In terms of data likelihood, RBMs allow us to learn the best possible projective MLN in the two-variable fragment. Furthermore, RBMs also admit consistent parameter learning over sub-sampled domains.
ARTIFICIAL INTELLIGENCE TRAINING OF FUTURE INDUSTRY 4.0 ENGINEERS USING LEGO MINDSTORMS IN FINAL DEGREE PROJECTS: AUTONOMOUS VEHICLE PROTYPE AS CASE STUDY

ARTIFICIAL INTELLIGENCE TRAINING OF FUTURE INDUSTRY 4.0 ENGINEERS USING LEGO MINDSTORMS IN FINAL DEGREE PROJECTS: AUTONOMOUS VEHICLE PROTYPE AS CASE STUDY
AGILE PRESENTATIONS IN HIGHER EDUCATION: PECHA KUCHA TECHNIQUE

Appears in: INTED2023 Proceedings Publication year: 2023Page: 6694 (abstract only)ISBN: 978-84-09-49026-4ISSN: 2340-1079doi: 10.21125/inted.2023.1796Conference name: 17th International Technology, Education and Development ConferenceDates: 6-8 March, 2023Location: Valencia, Spain
PRACTICE BASED AUTOMATION SYSTEMS EDUCATION

Appears in: INTED2023 Proceedings Publication year: 2023Pages: 1638-1643ISBN: 978-84-09-49026-4ISSN: 2340-1079doi: 10.21125/inted.2023.0462Conference name: 17th International Technology, Education and Development ConferenceDates: 6-8 March, 2023Location: Valencia, Spain
EXTENDED REALITY AS AN EDUCATIONAL TOOL FOR HIGHER EDUCATION INSTITUTIONS

Appears in: INTED2023 Proceedings Publication year: 2023Pages: 5335-5339ISBN: 978-84-09-49026-4ISSN: 2340-1079doi: 10.21125/inted.2023.1385Conference name: 17th International Technology, Education and Development ConferenceDates: 6-8 March, 2023Location: Valencia, Spain
INCREASING THE PUBLICATION ACTIVITY OF MASTER'S STUDENTS: THE CASE OF LOMONOSOV MOSCOW STATE UNIVERSITY

INCREASING THE PUBLICATION ACTIVITY OF MASTER'S STUDENTS: THE CASE OF LOMONOSOV MOSCOW STATE UNIVERSITY
IITU EXPERIENCE OF MOOCS USE IN THE EDUCATIONAL PROCESS

Appears in: INTED2023 Proceedings Publication year: 2023Pages: 5396-5401ISBN: 978-84-09-49026-4ISSN: 2340-1079doi: 10.21125/inted.2023.1402Conference name: 17th International Technology, Education and Development ConferenceDates: 6-8 March, 2023Location: Valencia, Spain
VALUE CLARIFICATION PROVIDED BY CHILDREN AT EARLY SCHOOL AGE IN LIGHT OF THE SOCIAL LEARNING THEORY

The purpose of the presented study is to show the clarification of values provided by the early school children in light of the social learning theory. The elements of the value clarification process as well as the opportunities provided by the application of the social learning theory of A. Bandura, who emphasizes the context of the value clarification provided by the school children of the elementary school younger grades, have been presented. In this regard, learning under the influence of consequences of own reactions and learning by modeling are worth mentioning. In the context of conducted analyses, the function of ethos and agos in the system of value clarification provided by the early school children has been highlighted.