Reviewerly/exHarmony huggingface dataset:
Deep Learning for Regularization Prediction in Diffeomorphic Image Registration

This paper presents a predictive model for estimating regularization parameters of diffeomorphic image registration. We introduce a novel framework that automatically determines the parameters controlling the smoothness of diffeomorphic transformations. Our method significantly reduces the effort of parameter tuning, which is time and labor-consuming. To achieve the goal, we develop a predictive model based on deep convolutional neural networks (CNN) that learns the mapping between pairwise images and the regularization parameter of image registration. In contrast to previous methods that estimate such parameters in a high-dimensional image space, our model is built in an efficient bandlimited space with much lower dimensions. We demonstrate the effectiveness of our model on both 2D synthetic data and 3D real brain images. Experimental results show that our model not only predicts appropriate regularization parameters for image registration, but also improving the network training in terms of time and memory efficiency.
Development of an Augmented Reality Application for Intuitive Infant English Learning

In this study, we developed an “English learning AR application for infants” that combines augmentedreality (AR) and deep learning by linking visually familiar objects with English words. Infants,who are the target users of this study, can visually learn the English words of an object as ARinformation by holding a smartphone over an arbitrary object. We constructed 57 types of self-madedatasets, prepared 200 images for each English word, and learned them 300 times. Additionally,we conducted a system evaluation questionnaire survey for 44 subjects to evaluate this AR application.After experiencing this application, the subjects evaluated the operability, relevance, readability,functionality, applicability, and learning effect. Because of the system evaluation questionnaire survey,although we could obtain high evaluations for many items, the result was that issues remainedin functionality.
Development of the content component of the methodology of formation of organizational skills of future chemistry teachers on the basis of the synergistic approach

The article considers the possibility of using the ideas of synergetics to develop a meaningful component of the methodology for the formation of organizational skills of a future Chemistry teacher, which allows the formation of appropriate professional and pedagogical competencies necessary for the organization and conduct of various types of school chemical experiments. This optimizes the process of forming such a quality of a future teacher as flexibility of thinking and will reduce the adaptation period of a novice teacher at school. The use of synergetic ideas in the educational and pedagogical process is considered in the context of the method. Based on the analysis of standard curricula on the subject of ‘Chemistry’, the main subject content of the chemical experiment was selected. The main task is to form a generalized ability toorganize and implement a school chemistry experiment by a teacher. At the same time, the actual content of the technique of the conducted chemical experiment may vary, but the main subject content must necessarily be covered. Examples explain the principle of discreteness, the possibility of a student choosing the topic for the development of a lesson, the topic of the analyzed lesson conducted by a fellow student, the topic of the lesson where they will perform the role of a laboratory assistant, the topic of case-study, the topic of the lesson with using a virtual laboratory, the topic of a home chemical experiment. The use of a synergetic approach will allow the student to feel like a ‘student’, ‘teacher’, and ‘laboratory assistant’, and also give the opportunity to perform the entire scope of laboratory work provided by the program. The teacher performs the function of a facilitator, organizing interaction and providing a methodological base. The article presents a model of the synergetic interaction of participants in the educational process. The synergetic approach to the development of the content component of the methodology allows it to flexibly respond to the rapidly changing demands of the current time and consider the personal preferences and interests of students.
The Economic Impact of Coronavirus Disease (COVID-19): A study on Tourism Indicators in the Kingdom of Saudi Arabia

Tourism is a spatial phenomenon based primarily on demand for various tourism products and destinations which vary among themselves based on the diversity of the geographical environments in which they are located. Of course, just as the prosperity of this activity is linked to the availability of the basic equipment for its establishment; it is not excluded that this recovery in tourism activity will decline due to several emergency natural conditions that are usually strong than the available human capabilities to overcome them. From this point, this study aimed to highlight some aspects of the economic impact of the emergence of Coronavirus (COVID-19) on tourism activity in the Kingdom of Saudi Arabia. The descriptive inductive analysis approach was used for the values of the general economic indicators of the country, as well as for the values of the tourism movement indicators, which include two main variables of tourism trips, as well as the values of tourism spending during the period from 2019 AD till 2021 AD. The analysis ended with a conclusion; The values of each of the general economic and tourism movement indicators in the study area declined significantly between the two years.
Penggunaan Abreviasi, Singkatan, dan Akronim dalam media WhatsApp di SMK Bina Sejahtera 1 Kota Bogor

This study aims to describe the form of abbreviations and patterns of word fragments used by Indonesian millennial teenagers in WhatsApp media. For example, the use of abbreviations and acronyms in communication. This fact is one of the novelties in the use of language. However, if the novelty is not limited in its use, it will be fatal, namely the loss of language function. The method used in this study is a content analysis method that examines a text or other communication media, one of which is WhatsApp media. According to Fraenkel and Wallen the definition of content analysis is content analysis, which is a technique that allows researchers to study human behavior indirectly, through the analysis of their communication. This study describes the formation and typology of abbreviations contained in WhatsApp media at SMK Bina Sejahtera 1 Bogor City. This study used descriptive qualitative method. The data in this study are all speech abbreviations and acronyms made by students of SMK Bina Sejahtera 1 Bogor City both orally and in writing. The data sources in this study were students of SMK Bina Sejahtera 1 Bogor City and the social media network WhatsApp. The factors that cause the use of abbreviations and acronyms among students of SMK Bina Sejahtera 1 Bogor City both in oral and written form, namely in oral form, the factor that causes is because they want to be considered a cool group because they have followed the times, dashing , slang, and not out of date, while in short writing, simple, saving words, words, and not wanting to follow EYD. WhatsApp is an internet-based application that allows each user to share various kinds of content according to the supporting features. The features contained in WhatsApp are gallery to add photos, contacts to insert contacts, camera to take pictures, audio to send voice messages, maps to send various map coordinates, even documents to insert files in the form of documents. All these files can be instantly sent through the free application. These various features certainly add to the ease and convenience of communicating through online media.&#x0D;
PENERAPAN ALGORITMA K-MEANS DALAM MENGATASI PERMASALAHAN SAMPAH (STUDI KASUS: POLA PERILAKU MASYARAKAT DALAM MEMBUANG SAMPAH)

Waste is discharged from a production process both industrial and domestic (household). According to the regulation number 18 of 2008 on waste management, it is mentioned that waste is the rest of the daily activities of humans or natural processes in the form of solid or semi-solid form of organic or inorganic substances. With the factors that cause damage to the environment because of waste, the Government of Makassar City with various shortcomings and challenges and obstacles experienced in handling the waste problem has also been fully aware of this. The local regulation on waste management of Makassar City, referring to the Regional Regulation of Makassar City Number 4 of 2011 on waste management. Classifying patterns of community behavior in disposing of waste to support the work program of the Makassar city government especially the Makassar Environmental Service to deal with waste management and environmental quality monitoring issues. This study aims to assist the Government of Makassar City in making programs to handle waste problems by applying K-Means Algorithm. The results of this study provide information on waste handling that takes place in the city of Makassar and reporting that helps and involves the Government and the City of Makassar's Office of Environment on the handling and management of solid waste regarding services and facilities that have been met.
Machine Learning and Deep Learning for Phishing Page Detection

The term "phishing" is often used to describe an attempt to obtain confidential data such as passwords or credit card details by impersonating a trustworthy source. In most cases, the term refers to attempts to trick users into providing sensitive information in response to a fraudulent email or web page. However, the term is also used to describe a broader category of online attacks to obtain sensitive information or to disrupt services or systems. Incorporating different machine learning and deep learning algorithms, including Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and random forest, the authors of this research presented a technique for identifying phishing websites. The data sets from PhishTank and the University of New Brunswick were used to train and test the learning models. The XGboost model was able to surpass most existing techniques by achieving a maximum accuracy of 86.8%. This technique can be used in modern web browsers like Google Chrome and Mozilla Firefox to accurately detect phishing websites.
Comparison of Nonlinearity Value of Substitution Box Generation Approaches

Substitution box (s-box) is one of the important structures that perform the mixing process for encryption algorithms. Therefore, strong s-box structures are needed to develop effective encryption algorithms. The most important feature of the S-box is that it has a nonlinear structure. In this way, it can effectively scramble the data to be encrypted. More than a hundred new algorithms have been proposed using many approaches to obtain s-box structures with high nonlinearity. In this study, the performances of the s-box generation approaches in recent years were compared according to their non-linearity values. In addition, the advantages and disadvantages of these approaches have been discussed and suggestions have been made especially for researchers who will just start in this field.
Detection of acute lymphocytic leukemia (ALL) with a pre-trained deep learning model

Acute Lymphocytic Leukemia (ALL) is a type of cancer caused by immature lymphocytes inthe bone marrow. Acute Leukemia is common in both children and adults. It can also cause death if leftuntreated. Hematologists diagnose ALL by examining the blood and bone marrow. This method used isslow and takes more time. In this study, the diagnosis and classification of the disease was carried out usingperipheral smear images with the proposed method. In the proposed method, 99.80% accuracy was obtainedby using the DarkNet19 pre-trained model. Then, 1000 features were obtained from Darknet19. 521 of theobtained features were selected with Mrmr feature selection algorithm. The selected features are classifiedwith support vector machines. An accuracy of 99.94% was achieved with the proposed method. The resultsshow that the proposed method can be used as a tool that will certainly assist pathologists in diagnosingALL and its subtypes.
Practical Perception-Based Evaluation of Gaze Prediction for Gaze Contingent Rendering

This paper proposes a novel evaluation framework, termed "critical evaluation periods," for evaluating continuous gaze prediction models. This framework emphasizes prediction performance when it is most critical for gaze prediction to be accurate relative to user perception. Based on perceptual characteristics of the human visual system such as saccadic suppression, this framework provides a more practical assessment of gaze prediction performance for gaze-contingent rendering compared to the dominant sample-by-sample evaluation strategy employed in literature, which overemphasizes performance during easy-to-predict periods of fixation. Using a case study with a lightweight deep learning gaze prediction model, we observe a significant discrepancy in the reported prediction accuracy between the proposed critical evaluation periods and the dominant evaluation strategy employed in literature. Based on our findings, we suggest that the proposed framework is more suitable for evaluating the performance of continuous gaze prediction models intended for gaze-contingent rendering applications.
FLAIRS-36 Invited Talk Abstracts

Three invited speakers for the general conference include Deborah L. McGuinness, Christoph Benzmüller and Bonnie J. Dorr. The special track invite speaker is for Nobal Niraula for the Applied Natural Language Processing track.
Farming Information and Interactive Technical Assistant using Android Service

This paper assists the personnel in charge of village events.It provides an interface for teams to store their data in order to conveniently organize awareness activities.They can develop event schedules, data needed for events such as power point presentations on seasonal crops, and related paperwork.Villager can send queries and ask suggestions to the professors.The objective is to develop an application which provides the details of various crops provided by government to the user.The goal is to create an application that automates the procedures and allows users to do numerous tasks.This project is mainly developed to provide details of crops and events provided to the users.This allows users to view their event information and its status to help user for better environment and friendly application.The mobile sector is currently one of the fastest expanding businesses.Many competitors in ths field are conducting research and development on new platforms and user experiences.Google's Android technology, which is supported by Google phones, is one such example.These handsets are referred to as Next Generation mobiles.This paper is mainly developed for improving the Farmers atmosphere.
Improving organizational performance

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Firms that increase their ability to innovate can boost performance. Desired outcomes become more attainable if leaders focus on specific dimensions of innovation orientation (IO) in order to positively affect knowledge management (KM) effectiveness in the company and improve its performance as a result. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.
Psychological Factors in Speaking Skills for EFL: A Case of Senior High School in Indonesia

The number of studies related to hindrance in speaking skills has been extensively conducted. However, psychological factors in EFL context were still under investigated. The study aimed at describing psychological factors that hinder students from speaking and the causes of the factors as well as the possible solutions to overcome the factors. The information was gathered through classroom observations, questionnaires, and interviews. According to the study's findings, psychological factors such as fear of making a mistake, shyness, anxiety, lack of confidence, and lack of motivation prevent students from speaking in English class. Those factors, like fear of making mistakes, were commonly caused by their fear of being laughed at by their friends. Most students believed that motivating them to be more confident in speaking English was a viable solution to overcome those psychological factors.&nbsp; This research shows that teachers need to pay closer attention to their pupils' barriers to speaking in class.
Implementation of fuzzy logic controller for TV viewing distance detector tool

This study describes the design of a safe distance detection device for watching TV using Arduino Uno. This system is expected to help reduce the risk of eye damage, especially those caused by viewing TV that is too close. This system functions to provide a warning in the form of an alarm where at a close distance the buzzer will activate and at a safe distance the buzzer will turn off. The system also provides warnings in the form of LEDs and LCDs as visual notification features, so that they can provide information to the audience to stay at a safe distance. In this study using the fuzzy logic method because this method is suitable for use in most real-time problems such as in making decisions to find variable and uncertain distances. With this fuzzy logic method, a mathematical framework is obtained that is used to represent uncertainty, ambiguity, inaccuracy, lack of information and partial truth.
Sparse adversarial image generation using dictionary learning

Adversarial examples are used to evaluate the robustness of convolutional neural networks (CNNs) to input perturbations. Researchers have proposed different types of adversarial examples that attack CNNs to fool them. These attacks pose a serious threat to applications that use deep neural networks. Existing methods for adversarial image generation struggle in maintaining a balance between attack success rate and imperceptibility (measured in terms of ℓ2-norm) of the generated adversarial examples. Recent sparse methods for this problem focus on limiting the number of pixels in an image but do not cater to the overall imperceptibility of the adversarial images. To address these problems, we introduce adversarial attacks based on K-singular value decomposition sparse dictionary learning. The dictionary is learned using feature maps of the targeted images from the first layer of CNN. The proposed method is evaluated in terms of attack success rate and ℓ2-norm. The extensive experimentation shows our attack achieves a high success rate while maintaining a low imperceptibility score compared to state-of-the-art methods.
A Case Study on the School Push Used for Learner-instructor Interaction

This study is a case study on investigating the possibility of the school push as a tool of learner-instructor interaction in untact education environment. To this end, one-sentence dictation using the push was implemented and one survey was conducted on a total of 144 students from two different English courses, 127 of whom responded the survey. The findings revealed that the push is effective for instructors to communicate with students in that it has high accessibility as MIM and school-based app. However, making the push be a more useful tool requires for instructors to be committed to communication with their students, to be well informed about the strengths of the push for its promotion, and to provide comprehensive introduction on how to use the push and check if students use it well.
Motivation and Effectiveness of Participating in Theme-Based School Education of Culture Art Project: Focusing on artists and teachers

This study was conducted to investigate the motives and effects of artists and teachers who participated in the ' Explore Life through Art' support project for school education by theme of culture and arts. As a result of research analysis using online survey and in-depth interview research method, it was found that both intrinsic and extrinsic motives have a complex effect on artists and teachers' motivation to participate in the project. As for the effectiveness of participating in the project, the trust between artists and teachers and the contribution of education were positive, but the trust and satisfaction with the institution were negative. In order to increase the effectiveness of the project, it is required to improve the operation and management of the operating institution. Motivation and effectiveness of project participation are important factors in improving the quality of a project, and it is hoped that this study will serve as a basis for practical discussions on the role of operating institutions and projects.
Malaria Detection in Blood Smeared Images Using Convolutional Neural Networks

Abstract: With 200 million cases annually, malaria often claims more lives than crisis and deadly wars. Given the ineffectiveness of efforts to lower mortality rates, insufficient malaria diagnosis is one of the hurdles to a successful and efficient reduction in fatality. Hence, malaria is one of the major causes of deaths and diseases in many developing countries, where young children and prenatal mothers are the most impacted populations. The parasite called Plasmodium is the source for the potentially fatal disease named malaria. Highly trained and experienced microscopists observe minute blood smeared images to look for the parasite. Modern deep learning techniques could automate the completion of the required analysis. With the development of an independent, accurate, and useful model the demand for skilled staff can be significantly decreased. In this study, we offer a totally automated method and approach for the diagnosis and classification of malaria using microscopic blood-smeared pictures based on convolutional neural networks-(CNN).
Sonic Play

Abstract “Sonic Play” presents “Intertwining” and “Albers,” two musical archetypes that are rhythmically similar but melodically different. Both archetypes are reminiscent of a moto perpetuo, steady yet always driving forward. Their construction allows the two hands to combine stability and mobility. The archetypes are easy to play and easy to transpose, as their fingerings and intervals are the same in every key; they’re also easy to vary and embellish. Varied and transposed, the archetypes can then be used as sonic Lego-like bricks with which the pianist can build improvisational and compositional sequences. Besides presenting improvisational games with easy-to-follow rules, the chapter includes multiple compositions employing the original archetypes. Some of the compositions are quite short and suited to a beginner’s exploration, and others are longer and more ambitious. The chapter covers transpositions by a minor third up or a major third down from an original key, enharmonic transpositions, and sympathetic resonances built into the archetypes.