Reviewerly/exHarmony huggingface dataset:
Two Heads Better than One: Dual Degradation Representation for Blind Super-Resolution

Authors:
raw_author_name: Hsuan Yuan
raw_affiliation_string: National Yang Ming Chiao Tung University
raw_author_name: Wei-Chen Chiu
raw_affiliation_string: National Yang Ming Chiao Tung University
raw_author_name: Yu-Syuan Xu
raw_affiliation_string: MediaTek Inc
raw_author_name: Jen-Hui Chuang
raw_affiliation_string: National Yang Ming Chiao Tung University
raw_author_name: Ching-Chun Huang
raw_affiliation_string: National Yang Ming Chiao Tung University

Abstract: Previous methods have demonstrated remarkable performance in single image super-resolution (SISR) tasks with known and fixed degradation (e.g., bicubic downsampling). However, when the actual degradation deviates from these assumptions, these methods may experience significant declines in performance. In this paper, we propose a Dual Branch Degradation Extractor Network to address the blind SR problem. While some BlindSR methods assume noisefree degradation and others do not explicitly consider the presence of noise in the degradation model, our approach predicts two unsupervised degradation embeddings that represent blurry and noisy information, respectively. The SR network can then be adapted to blur embedding and noise embedding in distinct ways. Furthermore, we treat the degradation extractor as a regularizer to capitalize on the differences between SR and HR images. Extensive experiments on several benchmarks demonstrate that our method achieves SOTA performance in the blind SR problem.
Tuning the initial phase to control the final state of a driven qubit

Authors:
raw_author_name: Sergey N. Shevchenko
raw_affiliation_string: B. Verkin Institute for Low Temperature Physics and Engineering, Kharkiv 61103, Ukraine
raw_author_name: Franco Nori
raw_affiliation_string: Department of Physics, The University of Michigan, Ann Arbor, Michigan 48109-1040, USA; Quantum Computing Center, RIKEN, Wakoshi, Saitama 351-0198, Japan

Abstract: A driven quantum system can experience Landau-Zener-St\"uckelberg-Majorana (LZSM) transitions between its states when the respective energy levels quasicross. If this quasicrossing is traversed repeatedly under periodic driving, the trajectories can interfere either constructively or destructively. In the latter case, known as coherent destruction of tunneling, the transition between the energy states is suppressed. Even for the double-passage case, the accumulated phase difference (also referred to as the St\"uckelberg phase) can lead to destructive interference, resulting in no transition. In this paper, we discuss a similar process for the single-passage dynamics. We study the LZSM single-passage problem starting from a superposition state. The phase difference of this initial state results in interference. When this results in either a zero or a unit transition probability, such a situation can be called single-passage complete localization in a target state. The phase can be chosen so that the occupation probabilities do not change after the transition, which is analogous to the problem of transitionless driving. We demonstrate how varying the system parameters (driving velocity, initial phase, initial detuning) can be used for quantum coherent control.
The Electronic Boycott of Foreign Products and its Impact on the Purchasing Rate of the Jordanian Consumer for Products from Beirut Lights Company for Hygienic Paper Manufacturing

Authors:
raw_author_name: Mahmoud Afeef
raw_affiliation_string: Assistant Professor, Marketing Department-Al Baha, University, Saudi Arabia P O. B. 1988 Patio Saudi Arabia

Abstract: This study investigated the effect of an electronic boycott of foreign products on the purchasing rate of Jordanian consumers for products from Beirut Lights company for hygienic paper manufacturing. This study collected data from 310 consumers purchasing products from Beirut Lights Company for Hygienic Paper Manufacturing using questionnaires. This study employed the Partial Least Square Structural Equation Modelling (PLS-SEM) approach and analysed the data. The results revealed that electronic boycotts (consumer animosity, consumer ethnocentrism, consumer efficacy, and product judgment) have significant and positive effects on purchasing rates. The results revealed that a 1% increase in Consumer Animosity would lead to an 18.5% increase in Purchasing Rate. Additionally, the results demonstrated that Purchasing Rate would increase by 15.2 percent with a 1% increase in Consumer Efficacy. Also, the results revealed that a 1% increase in Consumer Ethnocentrism would lead to a 23.5% increase in Purchasing Rate. Similarly, the results revealed that a 1% increase in Product Judgement would lead to a 44.1% increase in Purchasing Rate. For Western multinational corporations focused on expanding their foothold in the world's biggest consumer market, this study's conclusions have crucial consequences for decision-makers and management. The suppressed and intense emotion of hostility, which is a remnant of past hostilities, needs much more attention from the Beirut lights firm, which manufactures hygiene paper in Jordan. In other hostile market scenarios, the conclusions of this examination may be applicable to a strategic study of the boycott model.
Digital Systems Teaching and Research (DSTR) Robot: A Flexible Platform for Education and Applied Research

Authors:
raw_author_name: Joseph Morgan
raw_affiliation_string: Texas Space Technology Applications and Research (T STAR) LLC 216 W. 26th St, Suite G2, Bryan, TX 77803, USA

Abstract: The DSTR (pronounced "Disaster") robot has a strong history of being adaptable to different user's needs, and there are many opportunities ahead that indicate that the sky, quite literally, is not the limit for this robust platform.This paper provides a historical perspective on the development of the DSTR robot as a collaborative design developed by the Mobile Integrated Solutions Laboratory (MISL) at Texas A&M University and ASEP 4X4 Inc.Texas Instruments has been a major partner in the integration of the control electronics, and Texas Space Technology Applications and Research (T STAR) LLC has played a significant role in the propagation of the DSTR robot as an adaptable applied research/education/STEM outreach platform.The paper will present examples of the strong industry-academic relationships that allow the DSTR robot to be utilized in a multitude of experiential learning environments.In addition to a number of STEM outreach activities, the DSTR robots are being used in the Introduction to Engineering course at Blinn College and in the Freshman Engineering curriculum at Texas A&M University.DSTRs have also been selected by NASA scientists as a low-cost lunar sample collector.The paper will also discuss the newly developed DSTR-E (DSTR Engineering) unit which requires students to perform several engineering tasks during the build process.The paper will also include the lessons learned from initial design through its transfer to the private sector for commercialization and future plans.
The Role of Computer Technologies in Music Teacher Training: Implementing the Humane Education Strategy

Authors:
raw_author_name: Tetiana Borysova
raw_affiliation_string: Candidate of Pedagogic Science, Associate Professor at the Department of Music, Kamianets-Podilskyi Ivan Ohiienko National University
raw_author_name: Viktoriia Fedorchuk
raw_affiliation_string: Doctor of Philosophy in Educational Studies, Associate Professor at the Department of Pedagogics and Management of the Educational Establishment, Kamianets-Podilskyi Ivan Ohiienko National University

Abstract: The ever-evolving nature of society dictates educational policies, which is mirrored in the challenges of training music teachers in higher education. Pedagogical universities are constantly investigating ways to revolutionize education and introduce new pedagogical tools. This article analyzes the experiences, difficulties and directions of music teacher training in the scope of the humane education strategy. Surveying the condition of music education, its current status and potential for progress has demonstrated that the career of a musician-educator is and will remain in high demand as long as it is augmented with new professional content. This can be used to broaden the role of a music teacher in both regular and extra schooling, such as designing and implementing numerous musical and creative progression programmes. Importantly, the article delves into the issue of developing a model for teaching information technologies to future music teachers, which follows an interdisciplinary and context-oriented content selection principle. It advocates for a comprehensive approach to shaping a continuous sequence of educational subjects throughout the entire period of university education. It also highlights the integration of music and computer technologies as a means of teaching information technology and as a subject for study. Finally, the article highlights the significance of computer technologies in training future music teachers as there is a growing demand for music education specialists who are proficient in the technological processes associated with music software and can effectively employ computer technologies in their professional duties.
When University Met Industry

Authors:
raw_author_name: Liling Huang
raw_affiliation_string: George Mason University
raw_author_name: Matthew Gardner

Abstract: Abstract When University Met Industry Abstract With rapidly evolving technologies, the academia – industry collaboration on education and research has never been more important. Traditionally, academic institutions educate industry professionals before they enter the workforce, and the industry provides funding for universities on research projects. However, the current one-way flow of education and research can be enhanced by creating a more diverse and interactive dynamic to comprehensively address the ongoing challenges faced by both parties. This paper discusses the importance and challenges of industry and academic collaborations as well as strategies for successful academia – industry partnerships based on the newly established power engineering program at George Mason University.
Classification of Java Cities/Regencies Based on Human Development Index Using Discriminant Analysis and Naïve Bayes Classifier

Authors:
raw_author_name: Achmad Efendi
raw_affiliation_string: Department of Statistics, Faculty of Sciences, Universitas Brawijaya, Malang, Indonesia.

Abstract: Aims: This research aims at grouping of cities/regencies on the island of Java, where the central government as well as the most densely populated island in Indonesia, using linear discriminant analysis (LDA) and Naïve Bayes Classifier (NBC).&#x0D; Study Design: Quantitative design.&#x0D; Place and Duration of Study: Sample: The data used in this study is secondary data from the Indonesian Central Statistics Agency (Badan Pusat Statistik, BPS) regarding the 2022 Human Development Index (HDI) from 119 cities/regencies on the island of Java. The data used are four HDI indicators as independent variables (long and healthy living, knowledge, and the dimensions of decent living standards) and the HDI value as the dependent variable.&#x0D; Methodology: The grouping was carried out using LDA and NBC. LDA is a type of multivariate analysis used in the dependency method where the relationship between variables can be distinguished between the independent variable and the dependent variable. It aims at obtaining discriminant function equations to group cases into certain groups and to determine differences between groups based on independent variables. Meanwhile, the NBC method is a simple probability-based prediction technique based on the application of Bayes' theorem (Bayes' rule) with a strong assumption of independence.&#x0D; Results: Both LDA and NBC can be used for prediction and classification. Based on the results of the discriminant analysis, three discriminant functions were formed to group cities/regencies on the island of Java into three HDI groups. In the NBC analysis, the prior probability value for the very high category HDI group was 0.211, the high category HDI group was 0.606, and the medium category HDI group was 0.183. The research results show that LDA is better than the NBC for grouping cities/regencies based on the 2022 HDI indicators with an accuracy rate of 72.92%. Meanwhile, the NBC analysis only provides an accuracy of 64.58%. Three discriminant functions have been obtained to group cities/regencies on the island of Java based on the largest discriminant score where life expectancy makes the largest contribution in distinguishing each group.&#x0D; Conclusion: As a result, in this case LDA is a better classification method than the NBC. It is also of important to note medium class regions for further actions from stakeholders.
HP-FLDet: A High Performance Joint Face and Landmark Detector

Authors:
raw_author_name: Xueli Liu
raw_affiliation_string: Fudan University
raw_author_name: Ziqun Zhang
raw_affiliation_string: Fudan University
raw_author_name: Yao Liu
raw_affiliation_string: Alibaba Damo Academy
raw_author_name: Kexue Fu
raw_affiliation_string: Fudan University
raw_author_name: Xiao Chen
raw_affiliation_string: Fudan University
raw_author_name: Xinrong Chen
raw_affiliation_string: Fudan University

Abstract: Abstract Face detection and landmark localization are usually the fundamental and important steps of facial analysis. The accuracy degradation of any task has impacts on the accuracy and robustness of the downstream analysis. In most facial analysis systems, face detection and landmark detection, as two independent tasks, are predicted sequentially with single-task detectors respectively, which suffer from the higher complexity and poorer consistency. In contrast, multi-task joint face and landmark detectors are more efficient and have more shared features. However, when two tasks are predicted in one model, it is difficult to improve the accuracy of all tasks simultaneously, due to the different requirements of the different targets to be detected. In our opinion, the multi-task detection model, integrating the perception ability of both scale variation and detailed texture information for face and landmark detection, is arduous but important in unconstrained settings. In this paper, a High-Performance joint Face and Landmark detector(HP-FLDet) is proposed, which can predict facial bounding boxes and landmarks in single stage and improve the accuracy of both face detection and landmark localization simultaneously. In this detector, the context inception block and scale-aware multi-task strategies are designed to resolve extreme scale variance and improve the perception ability of detailed texture information. It demonstrates superior performance on both face and landmark detection datasets including AFW, PASCAL Face, FDDB, Wider Face and AFLW. Especially, it achieves SOTA results on the most challenging WIDER FACE dataset with 0.970(Easy), 0.963(Medium), 0.921(Hard) mAP on the test subset, which outperforms all state-of-the-art rivals.
Perspektif Belajar dengan Seni Tari Tradisional di Sekolah Menengah Pertama

Authors:
raw_author_name: Sri Wahyuni Syukur
raw_affiliation_string: STAI DDI MAROS

Abstract: This research aims to determine the perspective of learning with South Sulawesi Traditional Dance in Junior High Schools. This type of research uses qualitative research with an ethnographic approach. The subjects in this research were teachers and students at SMP Negeri 22 Bantimurung. The results of this research show that students who are already at the junior high school level have been equipped with sufficient knowledge to develop so that the learning process will be more challenging for teachers in order to increase students' interest and motivation to learn art in the classroom, one of which is by highlighting traditions and culture. Locally in the South Sulawesi area, namely the basic movements of South Sulawesi traditional dance. So, the role of arts education in junior high schools is an effort to improve students' abilities, especially in developing interests, increasing creative work, as well as knowing regional arts and the values ??contained therein. Through arts education, students are facilitated in the process of growth and development in three domains as learning outcomes, namely, cognitive, affective and psychomotor.
TRANS-CNN Based Gesture Recognition for mmWave Radar

Authors:
raw_author_name: Yuanhui Zhang

Abstract: In order to improve real-time performance of gesture recognition by micro-Doppler map of mmWave Radar, the point cloud based gesture recognition for mmWave Radar is proposed in this paper.Two steps are carried out for mmWave Radar based gesture recognition. The first step is to estimate the point cloud of the gestures by 3D-FFT and the peak grouping. The second step is to train the TRANS-CNN model by combining the multi-head self-attention and the 1D-convolutional network, so as to extract the features in the point cloud data at a deeper level to categorize the gestures. In the experiments, TI mmWave Radar sensor IWR1642 is used as benchmark to evaluate the feasibility of the proposed approach. The results show that the accuracy of the gesture recognition reaches 98.5%. In order to prove the effectiveness of our approach, a simply 2Tx2Rx Radar sensor is developed in our lab and the accuracy of recognition reaches 97.1%. The results show that our proposed gesture recognition approach achieves the best performance in real-time with limited training data, in comparison with the existing methods.
Fast Fake – easy to train Face Swap model

Authors:
raw_author_name: Tomasz Walczyna
raw_author_name: Zbigniew Piotrowski

Abstract: &amp;quot;Deep fake&amp;quot; technologies are often associated with face-swapping algorithms based on images or videos. Although much research is focused on developing these techniques, there is still room for improvement, especially in human and visual assessment. In this study, we present an innovative approach to the problem of face replacement based on one model while preserving background features. Our model uses the Adaptive Attentional Denormalization method from FaceShifter while integrating identity features from the ArcFace and BiSeNet models to support the attribute extraction process. We used Fast GAN as a generative model to optimize and accelerate the training process on smaller data sets. Our research proves the effectiveness of the proposed approach by combining innovative methods and architectures in one coherent solution.
PRODIGY: Probing Resilience Of Domain-wall Interactions at Gauge Theory

Authors:
raw_author_name: Matthew James Stephenson

Abstract: Examining the axion-dilaton model within supergravity, we focus on elucidating the construction and stability of domain walls. Emphasizing holographic vitrification action, we unveil insights into domain wall formation in gauge theories with periodic vacuum structures. Featuring a QCD-like axion term and a stabilizing dilaton, our model is scrutinized for conductivity changes under weak disorder. Notably, the system maintains perfect conductivity with a leading-order conductivity correction. Strong disorder emerges as the catalyst for transitioning to an insulator state. This study offers a comprehensive understanding of the axion-dilaton model's resilience and behavior under varying conditions.
A New 2D Cross Hyperchaotic Sine-Modulation-Logistic Map and Its Application in Bit-Level Image Encryption

Authors:
raw_author_name: Mingxu Wang
raw_author_name: Xianping Fu
raw_author_name: Lin Teng
raw_author_name: Xiaopeng Yan

Abstract: Chaotic theory is commonly being researched for application in image encryption scheme (IES). In this paper, a novel two-dimensional cross hyperchaotic Sine-modulation-Logistic map (2D-CHSLM) based on the famous Sine and Logistic maps. The hyperchaotic behaviors of 2D-CHSLM is testified with the help of their bifurcation diagrams, trajectory plots, Lyapunov exponents, sample entropy, C0 complexity, permutation entropy and 0-1 test. A new bit-level IES with traditional encryption structure is proposed utilizing 2D-CHSLM. The 2D-CHSLM-IES performs a 2D-CHSLM-based bit-level confusion using zig-zag transform and a 2D-CHSLM-based cross coupled diffusion operations for generating a highly secure cipher-image. Then the simulations and security analyses are further carried out with the help of key space, key sensitivity, histogram, correlation, information entropy, differential attack, noise and data loss attacks, prove that the security of the proposed 2D-CHSLM-IES
Peningkatkan Hasil Belajar Bahasa Indonesia Melalui Metode Role Playing

Authors:
raw_author_name: Erwin Eka Saputra
raw_affiliation_string: Universitas Sulawesi Tenggara, Kendari, Indonesia

Abstract: The problem in this classroom action research is that the low value of Indonesian through the role playing method can improve the speaking skills of Class V students at SDN 219 Ara, Bonto Bahari District, Bulukumba Regency. Bulukumba. The approach used is a qualitative approach. The type of research used is classroom action research which consists of two cycles, where each cycle consists of two meetings, with activity procedures including planning, implementation, observation and reflection. The subjects in this study were teachers and fifth grade students at SDN 219 Ara, Bonto Bahari District, Bulukumba Regency. Those who are actively registered in the odd semester of the 2012/2013 academic year have 10 students, consisting of 9 boys and 1 girl. Data collection techniques used are observation, tests and documentation. The data analysis technique used is descriptive quantitative analysis. The indicators of the success of this research are the indicators of the process and results of speaking skills. The results show that with the optimal application of the Role Playing method, student learning activities increase, this can be seen in the first cycle being in the medium category because it is seen from the results of the speaking skills test at the end of the first cycle where the average score The average student has not reached the predetermined KKM and in the second cycle is in the very high category. Thus there is an increase in students' speaking skills in Indonesian subjects after the implementation of the Role Playing method can increase.
An analysis of digital literacy skills of high school students in biology

Authors:
raw_author_name: Widi Purwianingsih
raw_affiliation_string: Universitas Pendidikan Indonesia
raw_author_name: Amprasto Amprasto
raw_affiliation_string: Universitas Pendidikan Indonesia

Abstract: &lt;p&gt;Digital literacy is a crucial skill for understanding information from various sources, such as the use of the internet and other digital media as a learning resource. Navigating the internet is an important skill to master to keep updated with the development of information and communication technology in the era of Industrial Revolution 4.0 and to master one of the 21st-century skills. Skills that someone should have in digital literacy include internet searching, hypertextual navigation, evaluating information, and synthesizing information. This study aims to determine the digital literacy skills of tenth-grade high school students in biology class. The research method follows the quantitative descriptive method. The population and sample were 62 tenth-grade high school students. The data collection technique is in the form of questionnaires focusing on four aspects of digital literacy. The results indicate that the digital literacy of tenth-grade high school students with an average score of 44% is in the fair category. Meanwhile, the results for each aspect of the digital literacy indicator obtained different scores, namely internet searching at 47% (fair), hypertext navigation at 27% (fair), evaluating information at 40.32% (fair), and synthesizing information at 60.48% (good). This research suggests how stakeholders can issue policies as a basis for improving students' digital literacy to support the learning process focusing more on 21st-century skills.&lt;/p&gt;