Reviewerly/exHarmony huggingface dataset:
Multi-scale features enhanced sentiment region discovery for visual sentiment analysis

Visual sentiment analysis intends to understand the sentiment evoked by images, which is an important yet challenging field. Existing methods focus on learning single-scale sentiment features from the whole image. However, it has been proved that image emotions are evoked by the sentiment-specific regions of the image, which are related to high-level to low-level sentiment features. To exploit multi-scale sentiment features from both holistic and localized information, we propose a novel end-to-end multi-task framework for joint sentiment- specific regions detection and sentiment classification. Our method contains three components: Multi-Scale Features Extractor, Sentiment-Specific Regions Detection Branch and Sentiment Classification Branch. In the Multi-Scale Features Extractor, by fusing multi-scale features extracted from convolutional neural networks by means of Feature Pyramid Network (FPN) and Adaptively Spatial Feature Fusion (ASFF), the proposed approach first generates a holistic feature carrying more sentiment-related information. Then, the semantic map is automatically discovered from the enhanced holistic feature by adopting attention mechanism in the Sentiment- Specific Regions Detection Branch, which does not require any manual annotations. Finally, the localized and holistic information are adaptively integrated for final sentiment classification in the Sentiment Classification Branch. Extensive experiments on public benchmark datasets demonstrate the robustness and effectiveness of our method in visual sentiment analysis.
USING TRADITIONAL WATER PUPPETRY IN VISUAL ART ACTIVITIES TO EDUCATE ON VIETNAMESE CULTURAL HERITAGE FOR CHILDREN OF 5-6 YEARS OLD

The article presents features of Vietnam’s traditional water puppetry and the educational significance of puppet shows. Through Analyzing the importance of cultural heritage for preschool children, the article provides educational orientations on Vietnamese cultural heritage through visual art activities in the kindergarten education program. The main content of the article presents the results of analysis of interviews and questionnaires with preschool teachers about the use of water puppetry in cultural heritage education for preschool children. On that basis, the article proposes ways to use water puppetry in visual art activities to educate children of 5-6 years old about Vietnamese cultural heritage, which are: Preparing the educational force; Choosing the right locations and art spaces; Selecting and integrating the educational topics; Determining content requirements for an introduction to the arts and socio-emotional development; Selecting the methods of organizing art introduction activities; Determining the necessary conditions for the child's receptivity.
Freaks by Brett Riley

Reviewed by: Freaks by Brett Riley April Spisak Riley, Brett Freaks. Imbrifex, 2022 [288p] Trade ed. ISBN 9781945501531 $18.99 Paper ed. ISBN 9781945501524 $14.00 E-book ed. ISBN 9781945501548 $9.99 Reviewed from digital galleys Ad Gr. 9-12 Micah and his three friends are bullied daily in school, so when one finds a dark magic book, the group decides to try to cast a spell that, at worst, will be a cool RPG sort of distraction, and at best could actually change their lives. Unfortunately, one of their vicious tormentors has come to cause more trouble at the exact moment a portal opens, so when the teens are endowed with incredible superpowers, he gets them too. All of their abilities will be needed, even those of their sworn enemy, to grapple with a terrifying beast that also came through the portal before it can violently murder everyone they love. The introduction of a government cover-up adds a layer of complexity, as the group tries to figure out who are their allies—if they have any. The bullying feels oddly old-fashioned, however, focused more on reading comics and the assumed limitations of being a girl rather than the digital jabs that make life miserable now. In addition, while it may be authentic that the four are not particularly kind to each other or developed outside of key traits, these elements make every single person in this novel difficult to relate to, let alone like. It is possible a sequel may give everyone some depth and growth, however, and readers who are mostly here for the portals, superpowers, and gory details of monster attacks will likely cruise right past the book’s flaws and leave satisfied with the action-driven plot. [End Page 228] Copyright © 2022 The Board of Trustees of the University of Illinois
It Takes Two to Tango: Design Thinking and Design Patterns for Better System Development

Design Thinking has become a well-established approach to solving wicked problems through creative and conceptual solutions. Thus, Design Thinking approaches usually end with finding novel solutions but do not offer support in the practical implementation of these solutions. To bridge the gap between finding creative solutions and implementing them into suitable end products, we see Design Patterns as a useful approach to combine the advantages of both sides—the human-centered Design Thinking approach and the practical implementation in system development. Design Patterns offer proven solutions to recurring problems and thus provide design knowledge to solve complex design problems. In this contribution, we demonstrate how Design Patterns act as a complement to Design Thinking by using the example of designing a lawful smart personal learning assistant. We use Design Thinking to extract the design solution of the lawful learning assistant and develop it with the help of Design Patterns. We demonstrate the use of Design Patterns by using the deletion routine Design Pattern as an example of how a Design Pattern can be used for lawful design in addition to their known fields of application in system development. The evaluation results show that the combination of Design Thinking and Design Patterns lead to an approach that not only identifies novel, complex solutions but also supports their practical implementation.
Transfer photo to anime with dual discriminators GAN

Anime is a popular art genre. Nowadays, the way of creating anime is mainly manual creation, which is a professional and time-consuming work. In recent years, though some methods, such as CartoonGAN and AnimeGAN, are proposed to transfer photos to anime images, there are still significant flaws: 1) The converted images are dark and the colors aren't vibrant. 2) There is potential for improvement in terms of the visual effect. To address these issues, firstly, we discussed the reasons why CartoonGAN and other approaches could learn anime style and proposed a novel method. It's based on the generative adversarial networks with dual discriminators and focus on texture style in grayscale space. Then, we ran tests on different datasets and obtained high-quality results. Finally, ablation experiments were used to further explain the effectiveness of our method.
Deep learning for optimization of e-evidence

The current scenario in the rise of Internet to solve the business problem is current trends, i.e., conducted through computers by physical storefronts. E-businesses use websites as essential transaction tools between different users. However, certain disadvantages are said to prevail when trade confrontations occur due to the maintenance of written evidence. E-evidence has become an extensive e-business requirement in the current era. As several agreements and paper logs associating the party privileges and contracts are stockpiled and publicized in electronic form, e-evidences have a significance in the negotiation and lawsuit of e-commerce quarrels. Standardization is considered a big question for e-evidence. Due to the absence of ubiquitous norms with the change in law enforcement, traditional learning mechanisms failed to form e-evidence. Deep learning has been applied with voluminous data by several firms for consent and observation. All data or information does not necessarily have a profound impact on integrating both Deep Learning and optimization mechanism. With the optimization and generalization of data, dimensionality and irrelevancy were minimized for law administration. The epidemic increase in data storage is a complication that must be handled in a cyber-sphere epoch where unlawful activities are continuously executed. However, it necessitates automating the analysis process with both deep learning and computer vision mechanisms. Automated deep learning and computer vision-based e-evidence categorization and recognition mechanisms simplified the entire process. E-evidence necessitates an authentication mechanism to safeguard the data or information in its basic form. The cohesion and genuineness of e-evidence, along with information processing, is considered a prerequisite. Besides, the sequence of e-evidence is said to be utilized in e-commerce quarrels.
Disease prediction and detection in animals by DNA genetic engineering using optical sensor based on silicon material

In our daily Life activities, every day we are observing atleast one person out of five is getting the deadliest disease Cancer. In this paper the diagnosis is carried on the Pet animals by using Optical Bio-Sensor. It is designed with a suitable Waveguide Structure. By using the Optical Waveguide structure, made up of Silicon material. By Passing the light through the Waveguide, light Confinement inside the Waveguide Structure, then analysis of the Quality factor is carried out. The different types of Cancer is studied & analysis is done. This analysis is done by using Analyte which is composed of DNA Micro-Array consisting of Proteins.
Morphological convergence as on-line lexical analogy

The English past tense contains pockets of variation, where regular and irregular forms compete (e.g.learned/learnt, weaved/wove).Individuals vary considerably in the degree to which they prefer irregular forms.This article examines the degree to which individuals may converge on their regularization patterns and preferences.We report on a novel experimental methodology, using a cooperative game involving nonce verbs.Analysis of participants' postgame responses indicates that their behavior shifted in response to an automated co-player's preferences, on two dimensions.First, players regularize more after playing with peers with high regularization rates, and less after playing with peers with low regularization rates.Second, players' overall patterns of regularization are also affected by the particular distribution of (ir)regular forms produced by the peer.We model the effects of the exposure on participants' morphological preferences, using both a rule-based model and an instance-based analogical model (Nosofsky 1988, Albright & Hayes 2003).Both models contribute separately and significantly to explaining participants' pre-exposure regularization processes.However, only the instance-based model captures the shift in preferences that arises after exposure to the peer.We argue that the results suggest an account of morphological convergence in which new word forms are stored in memory, and on-line generalizations are formed over these instances.
Naive Bayes Classifier (NBC) for Forecasting Rainfall in Banyuwangi District Using Projection Pursuit Regression (PPR) Method

Rainfall is one of the climates that has a big influence on life, such as aviation, plantations, and agriculture.Remote areas like Banyuwangi Regency are most likely to lack information on weather and climate data.Rainfall information in the future is also very decisive for the community in carrying out their daily lives, therefore prediction models or rainfall forecasting are very necessary for the community.This situation has encouraged the development of various models of approaches for forecasting rainfall.One approach for forecasting rainfall is the use of Global Circulation Model (GCM) data.GCM resolution is too low to predict local climate which is influenced by topography and land use, but it is still possible to use GCM to obtain local scale information if Statistical Downscaling (SDs) technique is used.SDs is a technique that connects GCM output as a predictor variable with local rainfall in Banyuwangi Regency as a response variable with an intermediary functional model.As for the GCM output response variable, there are three variables used in this study, namely rainfall, sea level pressure, and air temperature with a domain of 3×3 to 10×10.Forecasting rainfall in Banyuwangi Regency is carried out using the Projection Pursuit Regression (PPR) method.At the modeling stage with PPR, the optimum domain and many functions will be determined, where the chosen domain is the 6×6 domain and the optimum number of functions is m=6 with RMSEP value of 89.79.Furthermore, a process is needed to represent the forecasting results in simpler way, such as classification.The classification method used in this study is the Naive Bayes Classifier (NBC).Evidently, NBC uses PPR as a model produces forecasts classification with correct values for 18 months out of a total of 24 months with 75% of accuracy.
InnEO’Space PhD: Preparing Young Researchers for a successful career on Earth Observation applications

Abstract InnEO’Space PhD project is preparing young researchers for a successful career by developing modernised and transferable PhD courses and learning resources based on innovation skills and employers’ needs as well as in-depth knowledge of high stakes and approaches of Earth Observation in many application domains. The mains objectives of Inn’EO Space PhD are to enhance and develop researchers’ innovation-oriented mind-sets and skills through Earth Observation, raise awareness about employment opportunities in academia and industry among researchers and scientists, tackle future skills mismatches and create new synergies between PhD students and researchers and potential employers. The first action has been to develop the InnEOStartech where the program was set for European PhD students with the aim of developing their taste for entrepreneurship spirit through idea of founding a company or designing an application. The second action has been to develop a summer school that delivered both technical skills and soft skills, thus providing all the ingredients for an innovation-oriented mindset. From these activities we shall develop a series of SPOCs (Small Private Online Courses) that will be made available to the community for further dissemination and exploitation.
RESEARCH ON THE BALANCE OF REGIONAL HIGHER EDUCATION ECOSYSTEM IN CHINA

The balance of higher education ecosystem plays an important role in the sustainable development of regional higher education. Therefore, from the perspective of ecology of education, this paper intends to discuss the balance of regional higher education ecosystem in China and how to construct effective cooperation between universities and other subjects in the region. In order to solve the above problem, this research adopts literature study method and historical method, combed the domestic and foreign about higher education in education ecology and ecosystem research, summarized the development trend of China’s higher education and the development mode, and based on the symbiosis theory analyzed how universities and other main body to construct the effective cooperation. Through the above research, the following findings are obtained: 1) China’s higher education has moved from the elite stage and the popular stage to the universal stage; 2) Under the strong leadership of the government, China’s higher education has changed from extensional to connotative development mode; 3) The value orientation of cooperation between universities and government, enterprises, communities, other universities or research institutions is high-quality integration; 4) The cooperation path based on the symbiosis theory of regional higher education can provide a strong guarantee for the construction of a balanced higher education ecosystem.
Study on Steganography Concealing Data

Steganography is a process of hiding or concealing confidential information from unauthorized access. Steganography used in various fields such as military, aerospace and industrial applications. Steganography techniques are used for secure transmission of data from sender to receiver. The computer programmers, begins applying steganography techniques to video as well as audio files. This time multimedia data like image, audio, video are used as a cover media by steganography systems because public often send digital pictures in email and other Internet communication. The purpose of this review is to bring the idea of Steganography for young researchers.
KONFLIK TOKOH UTAMA DALAM NOVEL BERLATAR KELUARGA: KAJIAN PSIKOLOGI SASTRA

The research aims to produce a description of; the personality structure of the id, ego, and superego lead character in the novel "tears of God" by Aguk Irawan M.N. Research methods include; This type of study is a qualitative description. Data from this research in the form of quotations in the form of id, ego and superego lead character in the novel This Study using the method of data collection techniques and note the reading. As the instruments are key instruments as a researcher. The analysis of the data include data reduction, withdrawal of the presence data, and conclusions. Based on the results of the collection and the resulting data structure analyst personality Fisha Id in the novel consists of; helplessness, anger, anxiety, suffering, happiness. While the structure of the ego's include; sincerity, fear, obedience, patience, and acceptance. The superego structure include; acceptance, patience, do not despair, obedience, regret. From the results obtained from these three structures namely id, ego, and superego, shows that the bylaws Fisha always suffer, but suffering "endured with patience and admissibility with great resignation as Providence.
An effective image encryption algorithm based on a novel chaotic map

Cryptography based on the properties such as unpredictability and initial state sensitivity of chaotic systems is a strategy to improve the security of image encryption algorithms. In this paper, a Logistic Coupled with Sine (LCS) chaotic map is proposed, and it turns out that the proposed map has more complex behaviors than existing chaotic maps in terms of performance analyses. Furthermore, as a potential application, an efficient and effective image encryption algorithm is proposed based on the keystreams generated by this LCS map. In the encryption algorithm, for a given plain image, it is split by the parity of indices of image rows first, and then a new confusion-diffusion strategy is proposed to scramble and diffuse thoroughly the elements of these two divided parts of the image. The security analyses indicate that the proposed encryption algorithm has excellent statistical properties, high security and efficiency for image encryption.
Supporting FAIR* data discoverability in clinical research: building an object metadata repository of clinical trial objects

Title: Supporting FAIR data discoverability in clinical research: Building an object metadata repository (MDR) of clinical study objects Objective: The principal aim of the project is to combat the discoverability problem in clinical research by making all the various types of data objects generated by clinical studies easier to locate, and by describing how each of them
I CAN Do It: From GANs and Deepfakes to Art

Since GANs are effective in generating new data from existing examples, the natural question to ask is whether they represent a new step forward in machine creativity. To some extent, a certain (albeit limited and tightly circumscribed) idea of creativity is already central to machine learning in general—after all, at its heart ‘is the idea that an algorithm can be created that will find new questions to ask if it gets something wrong’—by learning from past mistakes, the algorithm tweaks itself so that it produces a better outcome next time (Du Sautoy, 2020, pp. 67–68). If displayed by human, such quality would likely be called creative thinking. Such ability is particularly acute in deep learning, which effectively involves the ‘rewiring’ of the entire neural network (or segments thereof) in the process, with such adaptability already manifesting the seeds of creativity within it.
Usage-Based Approach to Grammar in Korean Language Teaching and Learning

Grammar is the speakers’ internal knowledge of a language that enables them to speak the language. This internal knowledge is referred to as the cognitive organization of the speakers’ experience with language, which is the result of the response of the speakers’ mind to the ways the speakers use the language in communication. The main tenets of this usage-based theory of language are, among others (i) usage patterns are the main target of investigation, that is, in what context or contexts linguistic expressions are used and how and why; (ii) the frequency of a pattern matters, as its repeated use results in chunking, automatization, and categorization, and eventual language change; (iii) variations naturally occur as the result of language change, a process of creating and developing exemplars and old and new constructions competing and coordinating with each other; and (iv) a search for an account for diachronic and synchronic regularities is done through the study of grammaticalization. Given that the goal of language instruction is to enable the learners to communicate in the language they are learning (i.e., produce and understand it) as the ways the native speakers use it, grammatical descriptions in a language textbook should make reference to usages and usage patterns of the language, rather than what grammarians think generate ‘grammatically correct’ sentences. This chapter will examine samples of grammatical descriptions given in the major Korean language textbooks and evaluate their validity in terms of whether they truthfully and sufficiently reflect the usages and usage patterns of Korean.
TARS- AI based PersonalAssistant

The main goal of Artificial Intelligence is to provide effortless Human interactions with electronic devices such as computers which are simple and easy to use. Electronic communication has grown exponentially and demand has been found in current years. This new technology of impartial generation, artificial intelligence seeks to give computer connectors emotional states with related data and take into account the user&#x0027;s environmental and system consideration. Nowadays, Personal Assistants are used to carry out all the essential required tasks for day-to-day needs in fast growing area. Many companies have established different perspective of Virtual personal assistants based on their applications and areas such as Siri, Cortana, Alexa. In this work, we have developed a novel approach which can be used by every person as their own personal assistant. They can be customized the (gui) graphical user interface and set-up their assistants according to their need.
DEVELOPING COGNITIVE INTEREST OF STUDENTS IN MUSIC LITERATURE CLASSES WITH THE USE OF COMPUTER TECHNOLOGIES

The article presents the content of the multimedia set, which includes multimedia presentations, a test and a quiz, an electronic collection of music transcriptions and educational games. The article describes the diversity and versatility of the proposed set which proved to be successful in the development of students' cognitive interest according to the results of the experimental search study. The possibility of adjusting the processes of pre-professional training in organizations of additional music education due to the introduction of multimedia technologies in the educational process, the positive impact of which on the development of students' cognitive interest is confirmed by the results of an experimental search study.