Reviewerly/exHarmony huggingface dataset:
Dehazing method for transmittance correction

A new adaptive image fog removal model is designed, which combines multi-scale guided filter algorithm with hue model, in order to solve the problems that traditional methods can easily cause the result image to appear contrast loss, halo obvious, color distortion and color bias serious. The paper proposed a new transmittance estimation method which combines multi-scale guided filter and dark channel prior theory, aiming at preserve the color information belongs to the images better. In addition, a more efficient structure preservation filter is introduced to optimize the coarse transmittance distribution and improve the overall effect of the defrosting result image. As we can see during the result, when compared to the classic algorithm, the proposed method to this paper can not only achieves better fog removal effect, but also effectively suppresses halo and dispersion.
Doing More with Data

This book is designed for an undergraduate, one-semester course in experimental research, primarily targeting programs in sociology, political science, environmental studies, psychology, and communications. Aimed at those with limited technical background, this introduction to social science experiments takes a practical, hands-on approach. After explaining key features of experimental designs, Green takes students through exercises designed to build appreciation for the nuances of design, implementation, analysis, and interpretation. Using applications and statistical examples from many social science fields, the textbook illustrates the breadth of what may be learned through experimental inquiry. A chapter devoted to research ethics introduces broader ethical considerations, including research transparency. The culminating chapter prepares readers for their own social science experiments, offering examples of studies that can be conducted ethically, inexpensively, and quickly. Replication datasets and R code for all examples and exercises are available online.
EXAMINING THE EFFECTS OF PERCEIVED RISK ON CONSUMER’S ONLINE PURCHASE INTENTION IN KLANG VALLEY

This study examined the relationship between perceived risk and online purchase intention, including the roles of trust and subjective norms as a mediator and moderator in the relationship.A survey method was used to collect data and the hypotheses were tested using quantitative analysis.250 respondents completed the online survey, and the results were evaluated using IBM SPSS Statistics 26 and SmartPLS 3.3.3.Based on the findings, perceived risk was found to negatively affect online purchase intention and trust, while trust was positively associated with online purchase intention and significantly mediated the relationship between perceived risk and online purchase intention.Subjective norms were also found to moderate the relationship between perceived risk and online purchase intention.Thus, when the level of subjective norm is low, the relationship between perceived risk and online purchase intention becomes stronger.This study would be beneficial to the online vendors involved in e-commerce activities.Since many online vendors are still facing certain risks in their online businesses that would consequently affect their transactions and performance, they can use the insights gained from the findings of this study to have a better understanding of consumers and provide effective marketing strategies to enhance trust and reduce risks.
Analyzing and Modeling of the Influence of Lateral Vehicles on the Speed of the Moving Vehicle

When a vehicle is moving, its speed is affected by other vehicles in its lateral position. To explore the influence of the lateral vehicle on the speed of the moving vehicle, 30 video cases were extracted and indicators like speed, acceleration, distance were obtained. A decision tree model was used to analyze the importance of factors which affect the speed change of the moving vehicle. The results show that lateral distance at the moment of decision-making is the most important factor. When the lateral distance is not greater than 0.77 m, the speed of moving vehicle would decrease. Otherwise, the speed of the moving vehicle would increase or remain unchanged. According to the frequency distribution histogram, the speed variation of the decelerated samples and accelerated samples are both 1–3 m/s. This research characterizes the speed variation of the moving vehicle because of the influence of the lateral vehicle and contributes to new ideas for studying microscopic driving behaviors.
Blockchain User, Network and System-Level Attacks and Mitigation

This chapter is the first of two chapters providing a security and assurance technical discussion of currently known blockchain technology attacks. Whereas, in the next chapter, the focus is placed solely on smart contract vulnerabilities and attacks, this chapter covers blockchain vulnerabilities and ensuing attacks at the user, system and network level. The user-level attacks include stolen private keys and the use of blockchain-specific malware to initiate a security breach at the user-level. Readers are reminded that while all blockchain nodes are users, not all users are nodes. Node-level attacks stem primarily due to vulnerabilities associated with shared vulnerabilities and membership service provider (MSP) vulnerabilities. Furthermore, a total of eight node/network-level attacks and four system-level attacks are also presented and discussed. The chapter also provides readers with some suggested mitigation techniques for the various attacks discussed at each level (user/node/network/system). The chapter concludes with a discussion of some security best practices for each discussed attack, as well as a quick discussion of Ethereum, Hyperledger and Corda inherent security measures.
Energy Flow and Photons from Primary Coil to Secondary Coil of Transformer

The author proposed the mutual energy theorem in 1987 and the mutual energy flow theory since 2017. The theory of mutual energy has an axiom more than Maxwellâs equations, that is, the law of conservation of energy. The conservation of energy law is not Poyntingâs theorem, but an extension of the mutual energy theorem. Because of this new axiom, the new axiom conflicts with Poyntingâs theorem. In fact, it is also a conflict with Maxwellâs electromagnetic theory. The author believes that the law of conservation of energy should be adhered to, so Poyntingâs theorem or Maxwellâs classical electromagnetic theory should be appropriately modified. These works have been completed by the author in other papers. Recently, when studying the magnetic quasi-static electromagnetic field, the author found that the electromagnetic energy conservation law proposed by the author can be strictly proved in the magnetic quasi-static electromagnetic field environment. This is a great inspiration to the author. Based on the theory of magnetic quasi-static electromagnetic field, the author strictly proves the law of conservation of energy (mutual energy theorem) and the mutual energy flow theorem proposed by the author, and applies this theory to calculate the energy flow from the primary coil to the secondary coil of transformer. In order to simplify the problem, the author only calculates the mutual energy flow between two parallel current elements. The calculation results show that the mutual energy flow is generated on the primary coil and annihilated on the secondary coil. The properties of mutual energy flow are completely consistent with those of photons. It is also close to the photon model in Cramerâs transactional interpretation of quantum mechanics. The author believes that the transmitting antenna is consistent with the primary coil of the transformer, and the receiving antenna is consistent with the secondary coil of the transformer. The author believes that for the theoretical generalization from magnetic quasi-static electromagnetic field to radiated electromagnetic field, the law of conservation of energy, the theorem of mutual energy flow should guarantee and the time average value of self energy flow should be kept at zero. In this way, a new electromagnetic field theory which is different from Maxwellâs electromagnetic theory is obtained. Maxwellâs electromagnetic field theory adds displacement current, but it makes formulas such as the energy conservation law problematic in the case of radiation field. Maxwellâs electromagnetic field theory and mutual energy theory provide the same electric field, but the far-field part of the magnetic field (i.e. radiated electromagnetic field) is different. In addition, the electromagnetic mutual energy theory proposed by the author believes that the charge of the receiver produces an advanced wave. Advanced wave violates todayâs causality, but it is an objective physical existence.
New developments in artificial intelligence (AI)-powered products in marketing

Artificial intelligence (AI) has attracted much attention from various industries to facilitate their business process. One of the critical implications of AI in marketing is empowering products with this technology to enhance customer experience. Several practical examples of AI technologies, such as machine learning and deep learning, enhance product efficiency and effectiveness. While we could see a fast and massive improvement in this area, marketing literature is lacking behind this development in the industry. While the importance of AI in marketing literature is well documented, there is not enough accumulated knowledge of this development in a different product. Therefore, the present study aims to fill the gap by introducing the artificial intelligence-powered product (AIPP) concept to view development in this area. Thus, we define AIPP and industries that developed a customer product. Then, we review essential products in each of these industries and the role of AI in these products. This research contributes to marketing literature by providing accumulated knowledge of AIPP and marketing managers to understand recent advancements in AIPP in different industries.
Situation Analysis of Digital Literacy of Public-School Teachers in Punjab

The current study aimed at investigating the situation of digital literacy of public school teachers in Punjab. A self-prepared questionnaire was developed to examine the digital literacy of teachers in Punjab. The study focused on situation analysis of digital literacy of teachers that is helpful; to improving digital skills of teachers and analyzing the importance of digitalization and it's raising perspectives during COVID-19. The research study was carried out in 36 districts of Punjab, with 1000 teachers from the school education department participating as respondents. This was quantitative research. The results were analyzed using SPSS by independent sample t-test, ANOVA test, frequencies, percentage, means,and standard deviation. The opinion of respondents shows significant results regarding the importance of digital literacy for teachers and its rising perspectives. Through this situation analysis, the outcomes have also indicated that teachers should have good digital abilities, as the present situation of COVID-19 has changed the whole scenario of the world and digitalized education. So, it is a dire need to polish teachers' digital literacy skills in order to get effective outcomes in the realm of education.
Rotary transformer for image captioning

Image captioning tasks based on deep learning encompasses two major domains: computer vision and natural language processing. The Transformer architecture has achieved leading performance in the field of natural language processing, There have been studies using Transformer in image caption encoder and decoder, the results proving better performance compared to previous solutions. Positional encoding is an essential part in Transformer. Rotary Transformer proposed Rotary Position Embedding (RoPE), has achieved comparable or superior performance on various language modeling tasks. Limited work has been done to adapt the Roformer's architecture to image captioning tasks. The study conduct research based on the positional encoding of Transformer architecture, our proposed model consists of modified Roformer as an encoder and BERT as a decoder. With extracted feature as inputs as well as some training tricks, our model achieves similar or better performance on MSCOCO dataset compared to “CNN+RNN” models and regular transformer solutions.
An improved GMS image feature matching algorithm based on BEBLID descriptor

Aiming at the shortage of matching accuracy of ORB algorithm in image matching stage and the poor robustness of GMS algorithm under repeated texture conditions, this paper proposed an improved GMS image feature matching algorithm based on BEBLID descriptor. This algorithm firstly uses the ORB algorithm for image feature point extraction, secondly describes the feature points with BEBLID descriptor, after that discards false matching pair preliminarily by brute force matching. In order to improve the matching accuracy of the algorithm, two algorithms GMS and PROSAC are combined on this basis to obtain better matching pairs. The experimental results show that the algorithm has uniform extraction of feature points and high matching accuracy for different image feature matching, and its correct rate is improved by 10.97 percentage points to the GMS algorithm, which can meet the demand of large parallax image matching and improve the accuracy and efficiency of target acquisition in vision tasks.
The construction and function of high school career education electronic archives

The national education policy clearly points out that career planning guidance should be strengthened. This paper points out the necessity of constructing electronic files of high school career education from the three perspectives of national policy needs, teacher education and students' personal development, analyzes the characteristics of high school career education electronic files of development, multiple feedback and students' subjectivity, and proves that high school career education electronic files can help career education. Countries, schools and teachers can work together to jointly build high school career education electronic archives, students can according to different types of assessment tools, clearly laid high school three years of academic goals, giving full play to the advantages of its own expertise to realize the personalized development, high school education electronic files has positive significance to the development of students.
ICT in the Teaching and Learning of English as a Foreign Language: A Systematic Review of the Literature in the Dominican Republic

The development of education in the Dominican Republic has allowed teachers and management teams to carry out in-depth innovative work in guiding teaching and learning processes. The study makes a generalized vision of the types of technologies that lead to the formation of a foreign language. The purpose of the research is to inspire students in the formation of a non-native language, looking for alternative activities for the integration of a second language with the use of technology, promoting speaking, writing, listening and reading skills. The implementation of technologies inside and outside the classroom has promoted autonomous instruction, encouraging students to be independent and responsible for their learning processes in new educational environments.
PILOT STUDY OF SELF-ORGANIZATION AND THE FORMATION OF SOCIAL AND PEDAGOGICAL COMPETENCIES IN THE EDUCATIONAL ACTIVITIES OF STUDENTS

The article is devoted to the problem of psychological analysis of self-organization in the educational activities of modern students. Self-organization is the central link arising in the development of social and pedagogical competencies. The article discusses a pilot study of the criteria for the formation of self-organization and current methods of their study in the framework of socio-pedagogical competencies. Trends in the development of modern higher education are due to the global processes of integration of the world educational system, digitalization of the educational space, increased requirements for the quality of training specialists in a highly competitive labor market. Informatization, broad opportunities for obtaining knowledge, and involvement in the global educational process can benefit the subject of educational activity only if they possess the skills of self-organization, planning and self-control of activities.
A new digital material sharing method of multimedia network teaching based on 5G communication technology

To solve the problem of low efficiency of traditional network teaching material sharing, a new method of multimedia network teaching digital material sharing based on 5G communication technology is proposed. eXtensible Markup Language (XML) technology is used to design the digital material development model of multimedia network teaching. In order to realise the development of digital materials for multimedia network teaching, the material is packaged in modules. Based on 5G communication technology, a multimedia network teaching digital material sharing platform is developed to construct the shared service protocol and realise the efficient sharing of materials. The experimental results show that the proposed method has higher file transfer rate than the traditional method, better practical performance and better application prospect.
Pengembangan Literasi dalam Pembelajaran Bahasa

Literacy and language are two interrelated components. On this basis, language learning can be used as a medium in literacy development at schools, especially in reading and writing skills. Thus, to improve students' literacy performance, literacy-based language learning strategies need to be adopted including 1) building a literacy culture, 2) encouraging School Literacy Movement (GLS), and 3) choosing/implementing the appropriate approach/method. The strategy is a response to a number of findings that become challenges, as well as complex problems related to Indonesia's low student literacy, which ranks 62nd out of 70 countries (PISA, 2019).
Emitter for formation of nonlinear ultrasonic waves

The article is devoted to the development of a method for influencing aerosols with nonlinearly distorted wave packets of finite duration, determining the optimal characteristics of wave packets, before developing a new design of solid-state emitters of mechanical vibrations of ultrasonic frequency, determining the optimal geometric dimensions of these emitters and their relative position.
Distance education — a step into the future

The modern world of information technology does not stop improving for a minute. The emergence on the market of new types of gadgets, new programs, new IT market projects, technological improvement in the field of information technology finance contribute to the development of new technologies. The education sector was no exception. In the context of a pandemic, the educational process has undergone dramatic changes in terms of the methodology for conducting lessons, that is, distance education has replaced ordinary lessons. The article is devoted to the actual problem of modern education — distance learning. The main task of the article is to substantiate and substantiate distance learning as a new form of education. The article presents the main directions of development of distance learning, shows various electronic platforms. The problems solved by students and teachers at a distance are highlighted. It is shown that the effectiveness of distance learning is determined by the use of information technologies, which underlie the design and implementation of distance courses. It is concluded that the future education belongs to distance learning in the context of rapidly developing information technologies.
Multi-channel approach for secure optical image encryption

We propose a generalized encryption scheme suited for transmission of image data on multiple wavelength channels. Our key space size grows double-exponentially with number of channels, ensuring security against both brute-force and more sophisticated attacks.
Efficient Simulation of Broadband Non-Gaussian Quantum Optics Using Matrix Product States

We realize efficient full-quantum simulations of pulse propagation in highly nonlinear waveguides using matrix product states. As a demonstration, we study the quan-tum dynamics of an optical soliton, highlighting the emergence of non-Gaussian quantum features.
Inverse-Designed Optical Image Compression Metamaterials

For the first time, we present image redundancy reduction, that is image compression, through inversely-designed metamaterials. The optimized metamaterial performs passive image compression at the speed of light without the need of transistor-based computations.
Efficient Quantum State Tomography Using Collective Measurements of Two-Photon Polarization States

We implement a theoretical proposal by Massar and Popescu to demonstrate more efficient quantum state tomography using collective measurements. To do so, we project onto non-maximally entangled polarization states of two photons from the ensemble.
Fabrication Tolerant Inverse Design Grating Couplers for Scalable Trapped Ion Quantum Computing

A fabrication tolerant Si grating coupler for 1.762 µm operation is optimized with inverse design, allowing for −30 dB crosstalk between a pair of 133 Ba + trapped ion qubits within expected fabrication variation.
Characterization of the Entangled Photon State Before, During, and After a Proposed Two-Photon Absorption Event

An entangled state is spectrally and temporally characterized during a proposed entangled two-photon interaction. The measurement proves that for R6G single photon, classical scattering process is responsible for reported cross section disagreements between measurement approaches.
Triplet Filter Based on Reinforcement Learning for Relational Extraction

The annotated data set for relational extraction task is usually generated through distant supervision which results in model performance degradation due to noise data introduced. Most of the existing works eliminate the noise data at the sentence level. This paper proposes a model based on reinforcement learning to achieve noise reduction at triplet level. The model identifies the noise triplets with the feature encoding of the sentence and entity pairs of the triplets which are updated through the feedback from the relation extraction module. The experimental results show that the model keeps the correct triplets while identifying the mislabeled ones in the sentence, and finally improves the performance of relational extraction models.
Prosody Prediction with Discriminative Representation Method

Rhythm affects the naturalness and intelligibility of Text-To-Speech (TTS). However, rhythm prediction remains a great challenge, usually in two aspects: 1) the united annotation is a relatively difficult task, which depends on expert’s experience. 2) traditional methods based on conditional random field (CRF), which heavily rely on feature engineering, such as word segmentation, part of speech(pos) etc. For above problems, we propose a method to reduce the dependency for united annotation data and conduct the joint experiment which use one unified model on independent data. Meanwhile, we also propose an algorithm of Layer Look Up Table (LLUT): use an embedding layer to learn a discriminative representation for different level of prosody data without any feature engineering. By using this method, the classifier can share the parameters and predict for different prosody level separately, which reduces the number of trainable model parameters. In order to better represent the input text, we use the pre-training model, like BERT, to provide the semantic information. Our experiment shows that the method of LLUT, is better able to acquire the discriminative meaning of different prosody levels. And also, our algorithm is proved to be general for sequence annotation tasks thus we can do extra task, like polyphone-prosody prediction.