Reviewerly/exHarmony huggingface dataset:
Hybrid Method of Video Shot Segmentation Based on YCbCr Space Color Model

In this digital world, Video analysis is the most important and useful task. Currently, tremendous tasks have been done in video analysis like compressing the videos, video retrieval process and video database indexing, etc. For all these tasks, one common step is segmenting the video shots, which are referred to as Video Shots Segmentation (VSS). Video shots segmentation is used to segment the input videos into a number of frames sequentially where the scene changes occurred, i.e. called shots. In this article, segmenting the video shots follows a hybrid procedure. Here, we have introduced the moments of colors, distance metrics and threshold techniques. All the videos follow the above mentioned steps for segmenting the video shots. But, before that, the input video is converted into a specific color model i.e. YCbCr. Then, apply the color moments to extract the feature vectors of frames, which are differentiated based on the color features of frames. In every two frames of the video, distance metrics methods are applying to compute the similarity and dissimilarity of frames. And the dissimilarity of the frames can be computed by using the threshold technique to get the shots from the video. In this paper, we are using the adaptive threshold technique to segment the videos into various shots. In this step, we will get a true number of shots. By the experimental results, this proposed methodology can be evaluated with the sequence of videos based on the performance or evaluation metrics.
Pull a Robot out of the Hat: Should Works Created by Artificial Intelligence Be Protected by Copyright Law?

What happens when computers start doing tasks that have thus far only been performed by humans? For decades, AI has vibrated conversation amongst Intellectual Property Scholars. Whilst the conversation started as predictions for its future, understanding and regulating works created by Artificial Intelligence is increasingly a pressing issue. Painting is inherently a human ability, at least it was until now. Computers are now able to mimic the necessary emotions, experience and creativity necessary to produce paintings, indistinguishable from art made by humans. But is this enough to warrant copyright protection? Should the current copyright regimes protect works created by Artificial Intelligence?
Effective Density Visualization of Multiple Overlapping Axis-Aligned Objects

Large-scale analytics of multiple overlapping axis-aligned objects is a challenging computational geometry problem that can inform several applications and services, in diverse domains. The primary focus of this research is, given many axis-aligned objects, to devise efficient and effective data visualization methods that inform whether, where and how much they overlap. Currently, such visualizations rely on inefficient implementations to determine the size of the overlap of objects. We address this problem by exploiting state-of-the-art computational geometry methods based on the sweep line paradigm. These methods are fast and can determine the exact size of the overlap of multiple axis-aligned objects, therefore can effectively inform the visualization method. Towards that end, we propose OL-HeatMap, a novel density-based visualization technique that can be used to represent complex information about overlapping objects. Our experimental evaluation demonstrates the effectiveness of the proposed method in several synthetic and real-world data sets.
A Study on some modified Classical Ciphers for Secure Crypto-System

The Classical Cryptography in the ancient times is a way for secure communication without Computer technology. Developments in the research and technology provide secure communications so as to make the Cryptanalysis difficult. Several Classical algorithms [1] explain the secure cryptosystems for maintaining Confidentiality and difficulty in the process of Cryptanalysis. In this paper we proposed a modified multiple encryption scheme over Classical Ciphers, affine and Caesar Ciphers for secure communications.
Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu

AlphaZero has achieved superhuman performance on various perfect-information games, such as chess, shogi and Go. However, directly applying AlphaZero to imperfect-information games (IIG) is infeasible, due to the fact that traditional MCTS methods cannot handle missing information of other players. Meanwhile, there have been several extensions of MCTS for IIGs, by implicitly or explicitly sampling a state of other players. But, due to the inability to handle private and public information well, the performance of these methods is not satisfactory. In this paper, we extend AlphaZero to multiplayer IIGs by developing a new MCTS method, Action-Prediction MCTS (AP-MCTS). In contrast to traditional MCTS extensions for IIGs, AP-MCTS first builds the search tree based on public information, adopts the policy-value network to generalize between hidden states, and finally predicts other players' actions directly. This design bypasses the inefficiency of sampling and the difficulty of predicting the state of other players. We conduct extensive experiments on the popular 3-player poker game DouDiZhu to evaluate the performance of AP-MCTS combined with the framework AlphaZero. When playing against experienced human players, AP-MCTS achieved a 65.65\% winning rate, which is almost twice the human's winning rate. When comparing with state-of-the-art DouDiZhu AIs, the Elo rating of AP-MCTS is 50 to 200 higher than them. The ablation study shows that accurate action prediction is the key to AP-MCTS winning.
Human Tutoring Dialogues and their Analysis

This chapter describes our study of human tutoring. A corpus of tutor-student interactions was collected in the domain of Computer Science data structures: linked lists, stacks and binary search trees. These interactions were video recorded, and subsequently transcribed and annotated for multiple linguistic features of interest. The corpus was subsequently analyzed to discover the distributional properties of these features, and how they correlated with students' learning during the tutoring sessions.
Trainable generator of educational content

As the main problem of the research, the possibility of creating a universal educational platform that combines the possibilities of an online generation of educational content with the interface of the training process itself was considered. The methodology of the educational platform has been developed, in which the mass generation of content is carried out at random, based on simulation models of educational objects. A matrix interface is used, which allows performing custom operations by entering a sequence of typical operators. The system forms a reference base of operators, replenishing it from user solutions, which makes it possible to train and improve the system in order to provide methodological support to student users. An active demo layout of an educational content generator was created and tested, using the example of a specific problem from school mathematics. All methodological options function in the layout. There are three interface options: administrative, training and control. It was concluded that the approach based on the simulation of educational objects makes it possible to create a unified algorithmic platform that combines the functions of content generation with educational training. The system contains a unique option to teach yourself based on its interaction with students.
A Variational Perspective on Diffusion-Based Generative Models and Score  Matching

Discrete-time diffusion-based generative models and score matching methods have shown promising results in modeling high-dimensional image data. Recently, Song et al. (2021) show that diffusion processes that transform data into noise can be reversed via learning the score function, i.e. the gradient of the log-density of the perturbed data. They propose to plug the learned score function into an inverse formula to define a generative diffusion process. Despite the empirical success, a theoretical underpinning of this procedure is still lacking. In this work, we approach the (continuous-time) generative diffusion directly and derive a variational framework for likelihood estimation, which includes continuous-time normalizing flows as a special case, and can be seen as an infinitely deep variational autoencoder. Under this framework, we show that minimizing the score-matching loss is equivalent to maximizing a lower bound of the likelihood of the plug-in reverse SDE proposed by Song et al. (2021), bridging the theoretical gap.
The Relationship among Body Composition, Exercise Participation, and Perception towards a Lifetime Fitness Class in College Students

The current study analyzed the relationship between body composition and exercise participation, along with perception toward lifetime fitness (LF) classes in college students. Thirty-eight college students (20 males and 18 females) in a regional university completed a survey pertaining an LF class and exercise participation. Additionally, height, weight, waist-to-hip ratio, and body composition [fat free mass (FFM), fat mass (FM), and body fat percentage (BF%)] were assessed. Most males (65%) and females (77%) reported personal wellbeing as their main motivation to exercise (p = 0.021) outside of their LF class, rather than it being driven by a personal achievement motivation (35% males and 23% females). Males who exercise less than twice a week were associated with having lower FFM (p = 0.041), whereas females who exercise less than twice a week were associated with lower body mass index (p = 0.004), FFM (p = 0.027), and FM (p = 0.001). Although personal wellbeing was the main motivation to exercise for both male and female students, each sex has shown unique trends in its desires to participate in an LF class. Therefore, future LF classes should consider adopting curriculums that are able to uphold personal wellbeing motivation and account for unique needs and goals males and females may have in order to promote LF class engagement.
Fraud Detection System in Self-Checkout Centres

In the current digital era, the amount of time taken for any task to be done with the help of technology should be less. The growth of technology is so far wide that the solution to reduce the human workload and to reduce the time in processing of anything can be reduced. That is why while purchasing any item in a supermarket, people have to stand in a long queue in order to checkout with their items. So to reduce the time that is consumed as well as to reduce the labor charges of the retailer there is a self-checkout station which helps the customer to reduce their time during checkout. The customer can scan their items themselves and pay and go. Now the concept of fraud in here arises where there are some customers who to avoid paying for items they will try and act like they are scanning the items but in reality they are not scanning. And even if we try and question the customer it may sometimes happen that we catch the innocent customer and this reduces the trust level of the customer towards the retailer and the guilty ones get away with it. So this is where we come into picture. We have designed a system which will help the retailer to catch the customer who is trying to commit fraud. We have used an already existing dataset and with the help of that dataset we process various algorithms and try to find out which is giving us the best accuracy and with the help of that we predict whether or not the fraud is committed or not. And with the help of that processing we try and predict it with the real-time input. It means that when in real time the customer is trying to/acting like scanning the items the system will automatically detect it and the customer who is trying to commit a fraud will get caught.
접속 부사 ‘그러니까’의 의미 기능과 실현 양상

The purpose of this study is to analyze the use of the connective adverb ‘Geureonikka’ in actual language data and to describe the semantic function and realization aspect of ‘Geureonikka’. This paper analyzed the semantic function of the connective adverb ‘Geureonikka’ and its realization aspect by focusing on the realization aspect in the written corpus. ‘Geureonikka’ is a polysemous connective adverb which has meaning of ‘causal’ and ‘elaboration’, and there are similarities and differences between the two semantic functions. The ‘Geureonikka’ of ‘causal’ represents ‘foregrounded nature’, which is including new contents in the relationship with preceding contents by forming the relationship between preceding sentence and following sentence with ‘cause-effect’. On the other hand, the ‘Geureonikka’ of ‘elaboration’ is different since it has a ‘backgrounded nature’, which is not involved in the progress of the story by describing the same event or situation with homogeneity in a different expression method. (Yonsei University)
Note from the Editor on Unmanned Aerial Vehicles

A drone or Unmanned Aerial Vehicle (UAV) is an aircraft that does not have a human pilot on board. An Unmanned Aircraft System (UAS) comprises of a UAV, a ground-based controller, and a communication mechanism between the two. In terms of flying autonomy, UAVs can have varied degrees of autonomy. As opposed to crewed aircraft, UAVs were initially utilised for tasks that were too dull, unclean, or dangerous for humans. Aerial photography, package delivery, agriculture, enforcement and monitoring, infrastructure inspections, research, smuggling, and drone racing are just a few of the uses for drones, which were originally created for military use.
Il diritto all’identità dei figli in due recenti pronunce della Corte Costituzionale e della Corte di Cassazione

The identity of the person is an essential and distinctive element of his individual heritage and constitutes a real right. Two recent decisions, one of the Constitutional Court of May 2020 n. 127 and one of the Supreme Court, of September 2020 n. 19824, provided an opportunity to reflect on the issue of protecting the identity of children. In the first case of the child born from insemination heterologous and, in the second, of the child born of an anonymous mother, because, in both cases, there are significant problems of balancing the right of identity with other relevant rights or interests.
What to Accommodate to Develop Students' Academic Writing? Need Analysis for a Research-Based Textbook Development

The development of research-based learning proliferates throughout the world, and it depicts the growth of an academic article's publication globally. To strengthen the paper's quality, particularly in Indonesia, the students need a guideline on writing an academic article. This qualitative and quantitative research would portray the needs analysis in developing a research-based textbook in academic writing. Fifty students and thirty lecturers were involved in the interview, documentation, and survey. The result shows that the skills needed to accommodate are referencing skills, writing the research's significance, and writing the conclusion. This study also suggested nine units of an Academic Writing Textbook needed by the students to produce a good article, namely Introduction to Academic Article Writing, Strategies in avoiding plagiarism, Writing an introduction, writing a literature review, writing a research method, Presenting Findings and Discussion, Writing a conclusion, Tips on Referencing, choosing the title, and writing an abstract. These findings strengthen the previous studies, which states writing a conclusion of an academic article is challenging, particularly in the English Language Teaching context.
ENHANCING READING FLUENCY AND COMPREHENSION IN ORAL READING THROUGH READING THEATRE

Comprehension is the key of success reading. Researchers have shown that reading comprehension is improved when fluency increased. In order to construct the meaning of the text, instructional strategy which helps English language learners decode word until they fluently read and understand must be applied. This paper focuses on discussing the effects of using Readers Theatre as strategy to enhance English language learners fluency and comprehension in oral reading. It also provides the overview of the use of repeated reading. Readers Theater in particular, the role of fluency and comprehension in reading and the correlation about how fluency influences reading comprehension.
Simon Susen (2020) ‘No Escape from the Technosystem?’, Philosophy & Social Criticism, 46(6), pp. 734–782.

The main purpose of this article is to provide an in-depth review of Andrew Feenberg’s ‘Technosystem: The Social Life of Reason’ (Cambridge, MA: Harvard University Press, 2017). To this end, the analysis is divided into two parts. The first part gives an overview of its thematic structure and elucidates its key arguments. The second part discusses its most controversial aspects and grapples with its principal weaknesses and limitations. By way of conclusion, the article argues that Feenberg’s book demonstrates the pivotal role that the technosystem plays in shaping contemporary society.
Trust and the Digital Economy: A Framework for Analysis

The aim of this chapter is to provide insights into the state of the art of the digital economy and digital trust. Using a critical evaluation of literature on the topic of over 70 peer-reviewed articles, this paper provides an overview of the literature. The final result is the development of a digital trust model. Future studies should focus on empirical research on digital trust based on the proposed model, which can be carried out among different groups of entities.
Using the digital potential of education (based on the working experience)

The paper analyses the information openness of universities in accordance with the requirements provided by the current legislation of the Russian Federation in the field of education. It also considers the organization of educational activities carried out by universities and providing access to information and educational resources for students and scientific-pedagogical staff. The stages of digital learning units’ development within the framework of university courses are considered. Functional strategies for planning and conducting remote and in-class learning are investigated by the example of teaching foreign languages at a non-linguistic/technical university.
Rapper T.I. charged by SEC in cryptocurrency scam

The regulator said in its complaint that T.I. -- whose real name is Clifford Joseph Harris -- sold cryptocurrency tokens using his Twitter account and encouraged his followers to invest in the 2017 FLiK initial coin offering.
Polarity Shift Detection and Handling in Polarity Classification: A Survey

User-generated data over the internet is highly opinionated. Sentiment analysis is a task to extract opinions without losing any crucial information. Polarity classification is most researched from the last two decades under sentiment analysis. However, Polarity classification is a tedious job in natural language processing. There are certain circumstances where the polarity of the phrase differs from the polarity of words into it. This inconsistency is due to some trigger words that make the word polarity to get reversed. One of the main reasons for the performance degrade of the classification algorithm is the polarity shift. Polarity shift detection and handling approaches are applied to detect and handle polarity shifts, which can enhance the accuracy and effectiveness in classification. This paper gives a better understanding of the issue of polarity shift and surveys various methods of polarity shift detection and handling.
Prediksi Tingkat Kriminalitas Menggunakan Metode Single Moving Average (Studi Kasus Polres Asahan Sumatera Utara)

Crime is all kinds of actions and actions that are economically and psychologically harmful that violate the laws in force in the State of Indonesia as well as social and religious norms. Ordinary criminal acts affect the security of the community and endanger their lives and minds. The research location is the Asahan Police which is an agency that can provide security and protection for the community, especially those in Asahan Regency. The problem that occurs in this location is that there is no prediction system in Asahan Regency, due to the lack of knowledge factor in processing crime rate data. So it is difficult to know how much increase or decrease in criminal cases committed at the Asahan Police. The data used is data on cases of murder, sexual monitoring, tracing, violent theft, weight theft, motorcycle theft, fraud and counterfeiting money for the last 5 years in 2016 as many as 2020. Based on these problems, create a system for the crime rate in the Regency. Asahan to anticipate future crimes. The system that will be made uses forecasting or forecasting. With the Single Moving Average forecasting method. The Single Moving Average method is a forecast for the time in the future. The results of the calculation of criminal acts in 2021 found that there were 3 cases of murder, 2 cases of sexual intercourse in 2021, 252 cases of the 2021 return, 27 cases of violent theft in 2021, and 348 cases of bicycle theft in 2021. motorbikes in 2021 which open 90 cases, in 2021 which opens 85 cases, and money counterfeiting in 2021 which opens 1 case.
Use of Artificial Intelligence to Determine Copyright Liability for Musical Works

This article explores the use of artificial intelligence to help define the current test for copyright infringement. Currently, the test for copyright infringement requires the jury or a judge to determine whether the parties’ works are “substantially similar” to each other from the vantage point of the “ordinary observer.” This “substantial similarity” test has been criticized at almost every level due to its inconsistent nature. Artificial intelligence has evolved to the point where it can be used as a tool to resolve many of the current issues associated with the “substantial similarity” test. Specifically, courts would no longer have to rely on a battle of the experts or the use of lay observers to determine if a work is substantially similar to another work. Using a new test based on the “ordinary AI observer” copyright infringement can be established using a means that is both less biased and more fact driven while giving alleged infringers a means by which to check ex ante if their work could be infringing.
Peningkatan Kemampuan Membaca Pemahaman Cerita Anak melalui Penggunaan Model Pembelajaran Visualization, Auditory, and Kinestethic (VAK)

The aims of this research to improve the ability of reading comprehention children’s story through the use of learning models Visualization, Auditory, and Kinestethic (VAK). The type of research and the approach used is Classroom Action Research which is held in stages up to two cycles. The research procedure is also carried out in stages starting from planning, then continuing on the implementation of cycles I and II, observing, and ending with reflection activities. Non-test data collection techniques with observations, documentation, and interviews. The test technique was carried out from the results of the evaluation of the pre-action test, cycle I, and graded in cycle II. Students' learning completeness in the pre-cycle is 74.5% with an average of 76.5%, then in the first cycle it is 72.5% with an average number of 78.15 and in the second cycle it is 83.5% with an average number of 85.25. Therefore, the success obtained in this classroom action research was completed in cycle II.
Amazon rep says protesters 'not well-informed' about company's benefits, operations

Amazon is confident the majority of the workers are excited about the biggest deal day of the year.