Reviewerly/exHarmony huggingface dataset:
Combining Manifold Learning and Neural Field Dynamics for Multimodal Fusion

For interactivity and cost-efficiency purposes, both biological and artificial agents (e.g., robots) usually rely on sets of complementary sensors. Each sensor samples information from only a subset of the environment, with both the subset and the precision of signals varying through time depending on the agent-environment configuration. Agents must therefore perform multimodal fusion to select and filter relevant information by contrasting the shortcomings and redundancies of different modalities. For that purpose, we propose to combine a classical off-the-shelf manifold learning algorithm with dynamic neural fields (DNF), a training-free bio-inspired model of competition amid topologically-encoded information. Through the adaptation of DNF to irregular multimodal topologies, this coupling exhibits interesting properties, promising reliable localizations enhanced by the selection and attentional capabilities of DNF. In particular, the application of our method to audiovisual datasets (with direct ties to either psychophysics or robotics) shows merged perceptions relying on the spatially-dependent precision of each modality, and robustness to irrelevant features.
Post-Quantum Cryptography: An Introductory Overview and Implementation Challenges of Quantum-Resistant Algorithms

Cryptographic algorithms are an essential measure to ensure confidentiality and integrity of internet communication. The development of quantum computers (QCs) and their potential to utilize Shor’s Law, is increasingly recognized as a threat to asymmetric cryptography. In response, post-quantum cryptography (PQC) is gaining prominence as a notable field of research aiming to standardize quantum resistant algorithms before the operational usage of QCs. This paper is addressed to people with preliminary knowledge in the field of cryptography and QC. Based on a literature review, the authors provide an overview of challenges faced by the research community and elaborate the advancements in addressing post-quantum threats. A migration strategy from classical cryptosystems to PQC systems is in development, but obstacles such as time constraints and improper implementation complicate the process. Full implementation could take a decade or more. Until then, our paper aims to create awareness for potential challenges when transitioning towards PQC. As categorization scheme for these potential obstacles, we refer to a well- established model in cybersecurity – the McCumber Cube. Conclusions embrace preparing for risks of improper implementation and deriving a multi-step migration. Special attention is expected to be needed for data migration of existing data sets. As a request for future research in PQC, the authors identified the process of implementing post-cryptography standards, e.g., from the National Institute of Standards and Technology (NIST), and an assessment of the perceived readiness of industry to adapt.
IMPLEMENTATION OF MOORA METHOD FOR DECISION SUPPORT SYSTEM SCHOLARSHIP SELECTION IN SMK MUHAMMADIYAH PRAMBANAN

Decision Support System for Scholarship Selection at SMK Muhammadiyah Prambanan Using the MOORA Method aims to implement the Multi-Objective Optimization method on the basis of Ration Analysis. In determining scholarship recipients based on predetermined criteria and building a system in the form of a website to help provide alternative decisions in determining the acceptance of scholarships at SMK Muhammadiyah Prambanan. Based on the source of the data obtained, using primary data including interview and observation methods supported by secondary data obtained by literature studies that are relevant to the problem. Scholarship data is calculated and then ranked based on the final value generated from the MOORA calculation. The process of scholarships selection is based on criteria including report card grades, dependents of parents, the income of parents, percentage of attendance, and the number of siblings. The results of this study are the Scholarship Selection Decision Support System Using the MOORA Method, where the final value in the form of an alternative that has the greatest preference value will be placed at the top rank. The alternative will be a recommendation to receive a scholarship.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single Anonymous • Conference submission management system: EasyChair • Number of submissions received: 115 • Number of submissions sent for review: 88 • Number of submissions accepted: 80 • Acceptance Rate (Submissions Accepted/Submissions Received × 100): 69.6 • Average number of reviews per paper: 2 • Total number of reviewers involved: 12 • Contact person for queries: Name: Dr. Eng. Obie Farobie, M.Si. Email: obiefarobie@apps.ipb.ac.id Affiliation: IPB University, Indonesia
Marketing strategies and consumers purchasing behaviour in Ghana: A case of Nestle Ghana Limited

The role marketing strategies plays in influencing purchasing behaviors of consumers in various economies can never be overemphasized.However, this assertion requires further investigation with respect to consumers of Maggi seasoning products in Ghana especially those in Tamale metropolis.The study analyzed the effect of marketing strategies specifically sales promotion and perceived product quality on consumers' purchasing behavior toward Maggi products in the Tamale metropolis of Ghana.To achieve this goal, the study adopted the quantitative approach, descriptive design and structured questionnaire.Valid data sets were retrieved from 162 food vendors in Tamale Metropolis.The IBM SPSS Statistics software version 26 was employed to process the data and subsequently analyzed with both descriptive and inferential tools.The study found all the marketing strategies to significantly influence the purchasing behaviors of consumers of Maggi products focusing on food vendors within the Tamale metropolis, Ghana.As a result, the research found that marketing strategies, particularly sales promotion and perceived product quality, have a major role in encouraging consumers to make better purchasing preferences.According to the research, Nestle Ghana could use more comprehensive methods, such as unique sales promotion packages, better pricing, and better product concepts in order to guarantee high purchasing behavior among its clientele.
Pemanfaatan Hyperlink untuk Multimedia Presentasi pada Pembelajaran Teks Anekdot

This study aimed to provide an alternative multimedia option for learning anecdotal texts that are easy and cheap for teachers and interesting and memorable for students. Teachers get many choices in multimedia learning media, which are certainly the most in-demand by students in schools. This case is especially for learning anecdotal texts that have not yet developed. The research method used the development of Rusman, Dedi, and Cepi Microsoft PowerPoint. Researchers used observational data collection techniques, interviews, and documentation. The spiral techniques were employed to analyze the data. The validation results from 3 experts consisting of lecturers, teachers, and computer experts were obtained by 82% and 39 students by 84%. These results indicate that the product is feasible after development.
Utility of U-Net for the objective segmentation of the fibroglandular tissue region on clinical digital mammograms

This study investigates the equivalence or compatibility between U-Net and visual segmentations of fibroglandular tissue regions by mammography experts for calculating the breast density and mean glandular dose (MGD). A total of 703 mediolateral oblique-view mammograms were used for segmentation. Two region types were set as the ground truth (determined visually): (1) one type included only the region where fibroglandular tissue was identifiable (called the 'dense region'); (2) the other type included the region where the fibroglandular tissue may have existed in the past, provided that apparent adipose-only parts, such as the retromammary space, are excluded (the 'diffuse region'). U-Net was trained to segment the fibroglandular tissue region with an adaptive moment estimation optimiser, five-fold cross-validated with 400 training and 100 validation mammograms, and tested with 203 mammograms. The breast density and MGD were calculated using the van Engeland and Dance formulas, respectively, and compared between U-Net and the ground truth with the Dice similarity coefficient and Bland-Altman analysis. Dice similarity coefficients between U-Net and the ground truth were 0.895 and 0.939 for the dense and diffuse regions, respectively. In the Bland-Altman analysis, no proportional or fixed errors were discovered in either the dense or diffuse region for breast density, whereas a slight proportional error was discovered in both regions for the MGD (the slopes of the regression lines were -0.0299 and -0.0443 for the dense and diffuse regions, respectively). Consequently, the U-Net and ground truth were deemed equivalent (interchangeable) for breast density and compatible (interchangeable following four simple arithmetic operations) for MGD. U-Net-based segmentation of the fibroglandular tissue region was satisfactory for both regions, providing reliable segmentation for breast density and MGD calculations. U-Net will be useful in developing a reliable individualised screening-mammography programme, instead of relying on the visual judgement of mammography experts.
Creation of a Virtual Program for Infection Preventionist Training and Continuing Education

Methods: A full time IP position focusing on construction and facilities work was proposed to address a surge in construction activities and ongoing facilities projects requiring IP involvement.The goal was to provide consistent, standardized approaches to project management and build relationships with project managers and key leaders in Facilities.The IP visited all construction and facilities projects weekly to ask questions and learn about facility work standards and processes, while establishing relationships with the staff.Results: The IP helped fill the gap between IP's and key leaders in project management and the Facilities Department.Education modules were implemented for all contracted staff performing work in the facility.The IP established a tracking system for observations on all construction projects.Quarterly in-services are held to educate the Facilities staff regarding the impact of their work on patient safety.Regular meetings are held with key Facility leaders.Ongoing documentation of information pertaining to water intrusions and air handler work has been valuable during investigation of possible healthcare associated infections.Conclusions: This specialized IP role has provided much needed guidance and support to the Facilities Department and Contractors on site.This collaboration has helped ensure an emphasis on patient safety and infection prevention.
Transformer based Ensemble Learning to Hate Speech Detection Leveraging Sentiment and Emotion Knowledge Sharing

In recent years, the increasing propagation of hate speech on social media has encouraged researchers to address the problem of hateful content identification. To build an efficient hate speech detection model, a large number of annotated data is needed to train the model. To solve this approach we utilized eleven datasets from the hate speech domain and compared different transformer encoder-based approaches such as BERT, and ALBERT in single-task learning and multi-task learning (MTL) framework. We also leveraged the eight sentiment and emotion analysis datasets in the training to enrich the features in the MTL setting. The stacking based ensemble of BERT-MTL and ALBERT-MTL is utilized to combine the features from best two models. The experiments demonstrate the efficacy of the approach by attaining state-of-the-art results in all the datasets. The qualitative and quantitative error analysis was done to figure out the misclassified tweets and the effect of models on the different data sets.
Cosmusica: a Digital Musical Instrument for Interacting with the Universe

Cosmusica" is a new digital musical instrument that realizes the interaction between human and the universe.The gesture input and sound output of "Cosmusica" are located in two spaces of low earth orbit satellite and earth respectively.On the one hand, as the gesture input of the musical instrument, the silicone ball installed on the satellite solar panel moves slowly and irregularly under the influence of the microgravity environment of space, its motion trajectory is collected by the vision sensor and sent to the earth and restored as the performance gesture; On the
A Comprehensive study of digital Image Steganography Techniques

In the digital era of the internet, steganography is critical for data security. Steganography is a new field that is used to hide hidden information, and there has been a lot of research done so far. Based on the reviewed literature, this paper describes image steganography technology and its evaluation criteria. The main goal of this research is to demonstrate the potent influence of image steganography in concealing information regardless of media. If the PSNR is larger than 40db, imperceptibility is one of the essential evaluation requirements to ensure security
DECISION SUPPORT SYSTEM FOR PALM PLANTATION LAND SELECTION USING THE TOPSIS METHOD

Palm oil is an important export commodity in Indonesia. Quality palm oil is produced from quality oil palm plants as well. One of the factors to be able to produce quality oil palm plantations requires the right land. For this reason, land selection is an important factor. This study aims to develop a decision support system by implementing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for the selection of oil palm plantations. The TOPSIS method is a negative approach that is obtained by considering the shortest distance from the positive ideal solution and the farthest from the ideal solution. The system is built using a waterfall system development approach that starts from analysis, design, coding and testing. The developed system has the ability to manage alternatives, manage criteria, perform alternative calculations with TOPSIS, and display the best alternative results with TOPSIS. From the results of black-box testing, it proves that the developed system can work and run well. In addition, the results of manual calculations with the system show the same results.
Developing an Android Application for Social Media

Abstract: Social interaction has been the greatest social shift since the modern upset, drawing in huge number of individuals, making a consistently extending social web, and reforming the manner in which we impart. Yet many changes have occurred since the youth steps of casual correspondence and what it has formed into today, improvement is an endless cycle. Along these lines, in our task, extra strategies will be investigated to propel person to person communication generally. Web-based entertainment is a vital figure investigating present day culture in general, their qualities, standards, and ways of behaving, just like a piece of our regular day to day existence. It gives a phase where associations can get various crowds from all interests and sidestep different troubles like time, accessibility, openness, and distance of reach. The area is developing at a marvelous-rate
Detectsy: A System for Detecting Language from the Text, Images, and Audio Files

Abstract— Language detection is a natural language processing task where we need to identify the language of a text or document. As a human, we can easily detect the languages we know. However, it is not possible for an individual to identify many languages. This is where the language identification task can be used. The proposed solution is a complete system that detects language from the text, images, and audio files. Language identification task from text is carried out by training a Multinomial Naive Bayes classifier model. In the case of image and audio inputs, Python libraries are used to achieve the goal of language detection.
Test Construction Principles Violated in Selected Summative Tests in English

Teachers give many forms of assessment to measure their students’ performance and achievement. Paper and pencil test might be considered as an old and traditional form of assessment, but it is still effective until now. However, it has been observed that many test papers contain erroneous test papers. Thus, this descriptive study aimed to determine the test construction principles violated in sixteen summative tests in English gathered from high school teachers in a public secondary school in San Nicolas, Ilocos Norte, Philippines. Frequency counts and percentages were used to treat the data gathered. Interpretation and analysis of data were guided by the test construction principles used in the study of Lin (2002). Results of the study show that most of the vocabulary items violated the principle on making all the options with the same word class. On the other hand, the majority of the grammar test items used mixed options. When it comes to the reading comprehension section, most of the items can be answered from general knowledge. These test construction violations, in many ways, could hamper effective and successful assessments.
The Formation of Improvisation Skills in Future Bayan-Accordion Teachers in the Process of Performance Training

The article presents an experimental study aimed at developing the skills of improvisation in future teachers of bayan-accordion. The concept of improvisation and its influence on the development of creative abilities of a musician are considered. Improvisation has a great influence on the general professional level of development, namely the education of creative, well-developed musicians, develops musical hearing, sense of rhythm, musical memory, develops a good orientation on the keyboard, strengthens performance skills. Musicians feel confident during the stage performance, the ability to apply their own knowledge and skills in future pedagogical work are formed. The factors influencing the effectiveness of the development of improvisational skills are identified, the importance of a personal approach in accordance with the creative abilities of the student is emphasized. Attention is drawn to the need to use various improvisational forms and direct creative participation of the teacher in the process of working with students. Understanding the complexity and duration of this process, three stages of formation of improvisational skills were developed: motivational-oriented, reflective-informative, creative-activity. Each stage has a specific purpose and a clear sequence of actions, the principles of creative activities and independence, systematic and consistent, the unity of artistic and technical, as well as the development of various improvisational skills. The importance of musical thinking, constant auditory control for the implementation of tasks and the ability to transpose is emphasized. Due to the consistent application of certain stages of learning improvisation, creative and educational activities of students become universal.
Scene Classification, Data Cleaning, and Comment Summarization for Large-Scale Location Databases

This paper presents a framework that can automatically analyze the images and comments in user-uploaded location databases. The proposed framework integrates image processing and natural language processing techniques to perform scene classification, data cleaning, and comment summarization so that the cluttered information in user-uploaded databases can be presented in an organized way to users. For scene classification, RGB image features, segmentation features, and the features of discriminative objects are fused with an attention module to improve classification accuracy. For data cleaning, incorrect images are detected using a multilevel feature extractor and a multiresolution distance calculation scheme. Finally, a comment summarization scheme is proposed to overcome the problems of unstructured sentences and the improper usage of punctuation marks, which are commonly found in customer reviews. To validate the proposed framework, a system that can classify and organize scenes and comments for hotels is implemented and evaluated. Comparisons with existing related studies are also performed. The experimental results validate the effectiveness and superiority of the proposed framework.
Ways of compensation for nonverbal communication in SMS

Communication, generally, features not just a system in which the interaction takes place, but also a process, ways of communication, which enable creation, transmission and reception of various information. Nowadays, spoken communication is classified as one of the main types of communication; it is premised to use natural non-verbal and verbal channels simultaneously and in a seamless uniformity; written communication, which occurs as communicative activity among communicators by means of texts; non-verbal communication actualized by means of body language (facial expressions, gestures, etc.) and electronic communication – a relatively new way of communication – which, however, is actively penetrating modern life due to the opportunities which it presents. This article attempts to analyze lexical and syntactic units in English text messages, which help addressees to emphasize their emotional state in a written text while writing it; namely it attempts to demonstrate how non-verbal communication means are actualized via electronic communication. The analysis was carried out on the material of the messages in the Singapore variant of the English language – Singlish SMS – from the corpus SMS NUS. The English language is the dominant one in Singapore these days, prevailing over three other state languages: Chinese, Malay and Tamil. It is used in everyday life in interpersonal communication as a lingua franca and serves as a means of international communication and a means of uniting the country. Upon analysis some characteristic features of SMS messages have been identified, such as punctuation marks, pragmatic particles and interjections, expressions making up for registering the emotional state of the text author in writing.
Image Domain Generalization Method based on Solving Domain Discrepancy Phenomenon

&lt;p&gt;In order to solve the problem that the recognition performance is obviously degraded when the model trained by known data distribution transfer to unknown data distribution, domain generalization method based on attention mechanism and adversarial training is proposed. Firstly, a multi-level attention mechanism module is designed to capture the underlying abstract information features of the image; Secondly, increases the loss limit of the generative adversarial network，the virtual enhanced domain which can simulate the target domain of unknown data distribution is generated by adversarial training on the premise of ensuring the consistency of data features and semantics; Finally, through the data mixing algorithm, the source domain and virtual enhanced domain are mixed and input into the model to improve the performance of the classifier. The experiment is carried out on five classic digit recognition and CIFAR-10 series datasets. The experimental results show that the model can learn better decision boundary, generate virtual enhanced domain and significantly improve the accuracy of recognition after model transplantation. Comparing to the previous method, our method improves average accuracy by at least 2.5% and 3% respectively. Experiments on five classic digit recognition and CIFAR-10 series datasets which significantly improves the classification average accuracy after model transfer. &lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;