Reviewerly/exHarmony huggingface dataset:
Study on the Expression Methods to Communicate the Emotions in Messaging Application

In this study, we examined the relationship between “expression means” and “expression techniques” associated with the texts in the screen designs of the messaging applications and the emotional communication. First, we extracted the six types of emotion to be communicated, the four expression means, and the expression techniques for each expression means. After that, for each emotion, eight different screen design samples were created, and a questionnaire survey was conducted with 30 university students as subjects regarding the degree of transmission of the emotions. As a result of the analysis, it was found that although the specific expression means and the expression techniques differed in each emotion, they were generally effective in the expression means such as “the movement of the speech balloon and text”.
Investigating the Effectiveness of Web-Based Peer Review in Students’ Drafts Revision: A Critical EAP Perspective

Previous research on peer review considered it as a strategy of improving students’ writing (Baker, 2016; Hu, 2005). To investigate its effectiveness, this research has established a small corpus based on the data from the 22 students’ writing drafts and their corresponding written comments of 13,9261 words in total on the Peerceptiv National Writing and Feedback Contest (PNWFC). Then, Python was utilized as a tool to calculate the difference between four dimensions including accuracy, helpfulness, reviewing and writing. According to the quantitative analysis, it showed that students could hardly benefit from peer feedback. After that, three online structured interviews were arranged to further explore the development of English as a Second Language (L2) students’ discourse competence development. Given the consequence of qualitative data, students could revise their grammatical errors and language inaccuracies through peer review. They might implicitly develop their ability to think critically, which is the core of the formation of discoursal awareness in an English for Academic Purposes (EAP) course. More importantly, receivers could know of their weaknesses, and also perceive the accuracy and fairness of their discourses. Finally, essential implications might be helpful for teachers to carry out peer review and writing tasks in the future.
The Analysis of Arabic Language Textbooks for Class II Elementary School

Textbooks are one of the learning resources used in the learning process. As the main learning resource, textbooks serve as a medium for educators and students in an effort to achieve learning objectives. This study aims to describe errors in textbooks. The focus of the research was done by looking at syntactic errors, vocabulary, and writing Arabic words. The source of the data in this research is the Arabic book for Class II Madrasah Ibtidaiyah written by Sunaryo Putro published by PT. Three Series of Independent Libraries, Solo. The research method used is the method of content analysis with the analytical technique used is to record the types of errors contained in the textbook. The results showed that there were 13 errors in the textbook that the author examined with details of 3 errors in syntax, in the form of an error in the final vowel of a word that is not in accordance with its maqam i'rab, 3 errors in vocabulary (mufradat) which is the vocabulary in the book. not in accordance with the actual meaning, as well as 7 errors in writing words that do not refer to the writing of Arabic words that are good and correct, in accordance with the rules of Islamic science.
Using the Audubon Core Controlled Vocabularies for subjectPart and subjectOrientation

When the Audubon Core Multimedia Resources Metadata Schema*1 was ratified, it included two terms for describing what was being viewed in an image of an organism: ac:subjectPart, to indicate the morphological component of the organism included in the view, and ac:subjectOrientation, to describe the direction or viewing angle of the subject part relative to the image aquisition device. Although it was recommended that values for those terms come from controlled vocabularies, no such vocabularies had been created by TDWG. In 2019, the Views Controlled Vocabularies Task Group*2 was chartered to develop controlled vocabularies for these two terms. The result was two Simple Knowledge Organization System*3 (SKOS) concept schemes*4, 5, and a mechanism for determining which subjectOrientation values are appropriate for a given subjectPart and which subjectParts are appropriate for various organism groups. In this presentation, we briefly review the vocabulary development process, key features of the vocabularies, and give an overview of how the vocabularies can be used in several example cases.
Efficiency-optimized Data Perturbation in Local Differentially Private Federated Learning

Abstract Federated learning (FL) pours vitality into developing data-driven AI. However, there are still some challenges, such as balancing the security and efficiency in FL. Differential privacy is one of the dominant means in privacy-preserving machine learning. Local differential privacy (LDP) further realizes the confidentiality of the server by perturbing the transmitting parameters, which is naturally applicable for the decentralized FL. However, the current research exists the weaknesses of low communication efficiency and poor adaptability in complex deep learning models. In this work, we propose an efficiency-optimized LDP data perturbation mechanism (Adaptive-Harmony), which allows adaptive parameter range to reduce variance and improve model accuracy. Specifically, each client in each round adaptively selects perturbation parameters according to model training. Furthermore, only 1-bit data transmission for each dimension of the model parameters, thus significantly reducing the communication overhead. Theoretical analysis and proof have shown that Adaptive-Harmony holds the same asymptotic error bounds and convergence performance as advanced works but with minimal communication costs. An LDP-FL framework (Optimal LDP-FL) is also proposed, taking Adaptive-Harmony as the core. We also introduce a parameter shuffling in the Optimal LDP-FL, which avoids server tracking clients through the model parameters, thereby improving privacy levels without consuming the privacy budget. Comprehensive experiments on the MNIST and Fashion MNIST datasets show that the proposed method can significantly reduce computational and communication costs with the same level of privacy and model utility.
Hiding Secrets Using Quantum Entanglement

Three experiments demonstrate the key elements of a quantum cryptographic scheme that predictions indicate should be unhackable, bringing the promise of quantum encryption technologies a step closer to reality.
Curved Light Channels Have Better Coupling

More frequencies of light can pass between two coupled wavy waveguides than between two coupled straight ones, something that could allow for more flexible designs of optics-based circuits on silicon chips.
Improving Students Speaking Ability Through Story Telling

Learning in class tenth TKJ 1 about speaking is very low, students look embarrassed and are not confident in speaking English, this is due to the lack of opportunities for students to speak. With the total 32 of students and carried out starting on july 17 to 1 august through the method of classroom action that researchers do 2 cycle of the cycle 1 and cycle 2. The researcher use story telling method for train students speaking, PTK (Penelitian Tindakan Kelas) or Action Research is research practice for improve learning in the class. Iam is the researcher do PTK (Penelitian Tindakan Kelas). Score KKM (Criteria Completeness Minimum) in SMK BNI 76 and 75% total from the students, then the results of the test are pre-test tell stories directly without preparation in front of the the classroom only 8 students that reaches KKM, 25% from 32 students with average 66. Cycle 1 tell stories about holiday there are 19 students that reaches KKM, 59,3% with average 72,75, on cycle 1 not yet reaches KKM so the next on cycle 2. Cycle 2 tell stories about experiences the result 24 students that reaches KKM, 75% from 32 students with the mean 80,25.&#x0D; Keyword: Speaking Ability, Story Telling, Activity
Implementation of the Decision Tree Algorithm as an English Learning Media at SD Negeri 1 Senenan

This research is motivated by the declining interest of students in learning English because teaching the old or traditional way more or less hinders the ability of many students to understand certain languages. The purpose of this research is to design an English learning media in the form of educational games to attract students' interest in learning English further. This research uses the waterfall development method which is combined using the Decision Tree algorithm. In its application the Waterfall method has five stages, namely, Requirements Analysis, System Design, Program Code Writing, Testing, and Maintenance, while the application of the Decision Tree algorithm lies in the first game to choose what path or scan will each player get. The results of this study showed that 90.85% of people who took part in the survey through respondent questionnaires were interested in learning more English.
Biometrics Face Recognition Using Method of Wavelet and Curvelet Transforms with COVID-19

During last two decades the subject of face recognition has become a major issue. It has been used in several important real-world applications such as database security, video surveillance, smart card, internet and intranet. The people’s ability to recognize a face is reduced if the person has a mask covering the lower part of face, so it may be focus now on, the eyes and the individual features on upper part of face. To extract the features, the Wavelet and Curvelet transforms proved its efficiency due to its higher for detection of curves and lines, which recognize the human’s face, these features are used to identify the enrolled persons and it should be stored in the template system to be used later in the recognition system. The result of this paper is to recognize the face of person with mask. The system performance was evaluated depend on face database (kaggle) for face-recognition with face mask during COVID-19 period. The results indicate that the proposed system showed good results, and it outperforms the other algorithms that used in face-recognition.
Experiment Analysis on Fast Features Bag Approach for Pedestrian Re-recognition

Pedestrian re-recognition is a significant and challenging research topic in the field of multi-camera surveillance in smart transportation. This paper defines the important practical significance to improve the intelligent monitoring system. The feature representation and feature matching are two challenging factors in pedestrian re-recognition. In this paper, we improved the traditional bag of features algorithm due to its shortcomings, such as low classification accuracy and low computational efficiency. The main work of this paper is described as follows; First, we proposed the fast feature bag (FFB) method by using the SURF algorithm, which extracts the initial features descriptor and constructs a visual dictionary to handle with the influence factors e.g., light changes and scale-invariant. After that, we adopted the covariance descriptor method to the pedestrian re-recognition algorithm, which improves the matching accuracy in the few samples cases. Then, we used the LIBSVM classifier based on the FFB algorithm to improve the efficiency of the pedestrian re-recognition algorithm. By contrast with the CMC curve, we compared the proposed method with traditional mainstream algorithms by using pedestrian re-recognition datasets to prove that it is effective to solve the complex pedestrian re-recognition problems and perform better than the traditional methods in terms of matching efficiency and classification accuracy.
A Classifier Based on Gene Expression Programming

Classification is an important branch of Data Mining technologies. The purpose of classification is to construct a classifier, for training with the training data set, so as to construct a classification function to achieve the effect of the unknown data classification. The algorithm of classification in general can be realized by traditional algorithms like Naive Bayes, K-Nearest Neighbors, and Neural Network etc. This paper presents a special approach for constructing a classifier from a point of Gene Expression Programming, in which genetic process has been kept up as dealing with the regression problems. The proposed approach for constructing the classifier starts off with a digitization of category as the target value. Subsequently, the classification thresholds are set correspondingly in dealing with practical problems. The experimental results show that the Gene Expression Programming algorithm performs very well in classification, not only the binary classification but also three or more categories. The high performance observed and nice feature intrinsic (such as strong search capability and evolution competence) make the new proposal a promising tool for solving classification problems.
A Iconografia Editorial como nicho mercadológico para o Bibliotecário

The research analyzes the iconographic publishing market, as well as the practices relevant to librarians working in this field. The work routine of the niche is also observed in order to verify the existence of a symbiotic relationship with Librarianship. With this, it is proposed as a main objective to investigate how editorial iconography is established to the librarian's profile, highlighting, in turn, the contributions of librarianship praxis to the development of the iconographic market. The study has an exploratory character, a quantitative-qualitative approach and the procedures adopted were the bibliographic research and the application of a survey. The research presented the dynamics belonging to thesphere of editorial iconography and identified congruence with the activities equivalent to the practices developed by the librarian's know-how. Therefore, it is concluded that there is a market niche prone to librarianship based on their skills acquired by training as an information professional, which positively collaborates with the iconographic field.
Práticas transidiomáticas em tempos de globalização e superdiversidade: o uso da língua inglesa em propagandas em língua portuguesa

In face of the globalization process and the huge fluxes of pe- ople, texts, and cultures that has been made possible due to develo- pments in technology, the use of words in English in advertisements written in Portuguese has become common. In the field of Applied Linguistics, these uses are characterized as transidiomatic practices (MOITA LOPES, 2013). This research aimed to collect, analyze, and characterize transidiomatic practices in the surroundings of the EFL- CH campus, in Guarulhos. The corpus was collected through pictures to register real language uses; after that, it was separated in categories according to its themes. The methodology used was qualitative (DENZIN &amp; LINCOLN, 1994) in order to interpret the meanings of these uses based on the concepts of transidiomaticity, superdiversity, and World Englishes. The practices in the context studied involved mainly one or two content words in English in texts in Portuguese constituting hybrid and diverse language uses.
DNN Architecture for High Performance Prediction on Natural Videos Loses Submodule's Ability to Learn Discrete-World Dataset

Is cognition a collection of loosely connected functions tuned to different tasks, or can there be a general learning algorithm? If such an hypothetical general algorithm did exist, tuned to our world, could it adapt seamlessly to a world with different laws of nature? We consider the theory that predictive coding is such a general rule, and falsify it for one specific neural architecture known for high-performance predictions on natural videos and replication of human visual illusions: PredNet. Our results show that PredNet's high performance generalizes without retraining on a completely different natural video dataset. Yet PredNet cannot be trained to reach even mediocre accuracy on an artificial video dataset created with the rules of the Game of Life (GoL). We also find that a submodule of PredNet, a Convolutional Neural Network trained alone, reaches perfect accuracy on the GoL while being mediocre for natural videos, showing that PredNet's architecture itself is responsible for both the high performance on natural videos and the loss of performance on the GoL. Just as humans cannot predict the dynamics of the GoL, our results suggest that there might be a trade-off between high performance on sensory inputs with different sets of rules.
Mobile Robot Optimal Path Planning in the Configuration Spacebased on Smoothing A*

—Mobile robots have been widely applied in the industrial world. Mobile robots are proven to help humans work, especially repetitive ones. A robot needs to plan its trajectory to move as desired, a concept that requires path planning. Path planning is a non-deterministic problem that plays a role in finding a path to connect the system to the desired destination. The existing path planning algorithm proposes a path with sharp bends that make it difficult for the robot to maneuver so that it can still be optimized from the sides of the proposed path. One way is to make smoother turns so that the robot is not difficult to turn. Applying the interpolation method using b-spline makes the proposed path smoother. B-spline is a spline feature that provides a specific order and minimal support for domain partitioning. B-spline is applied to the Smoothing A*(SA*) algorithm, one of the breakthrough methods to produce smoother paths. As a result, SA* consistently produces paths shorter than the stateof-the-art by 0.957% and shorter than the baseline by 4.891%.
The Influence of Cryptocurrency Transaction as a Currency in NFT-Based Game Transactions

Cryptocurrency is a digital or virtual currency that is guaranteed by cryptography along with the emergence of cryptocurrency, the emergence of NFT is also widely discussed, NFT is referred to as a digital asset in the form of works of art or collectibles such as photos, pictures, videos, games and so on.Currently, cryptocurrency-based NFT games are being discussed as a transaction method, with the emergence of this transaction method reaping many pros and cons.To be able to find out the acceptance and use of Cryptocurrency methods in this NFT game.UTAUT is used as a research model UTAUT is a model to explain user behavior toward information technology.UTAUT is formulated with 4 core determinants of intention and usage, namely performance expectancy, effort expectancy, social influence, & facilitating conditions.This study used a questionnaire for sampling and obtained 244 respondents who had used the cryptocurrency transaction method in this NFT game.This study aims to prove the effect of independent variables (Performance Expectations, Effort Expectations, Social Influence, Perceived Risk, Trust, Facilitation Conditions) on the dependent variable (Behavioral Intentions and Usage Behavior).The results showed that there were positive and negative effects.Performance Expectations, Effort Expectations, Social Influences, Risks, and Facilitation Conditions have a positive and significant impact on Behavioral Intentions.Meanwhile, the Trust variable does not effect on Behavioral intentions, and Behavioral intentions have a positive effect on user behavior
The relationship between verb meaning and argument realization: What we learn from the processing of agent-implying intransitive verbs in Japanese

This study investigated whether some Japanese intransitive verbs, called agent-implying intransitive verbs, are processed differently from other ordinary intransitive verbs. These verbs are special in that they denote agentive events, but they are intransitive verbs, which only allow the patient/theme to be the only nominatively marked argument. The priming experiment was designed based on the situation model theory, assuming that verbs with an agentive semantic structure (e.g., ordinary transitive verbs) has a shorter causal inferential distance than those with a non-agentive semantic structure (e.g., ordinary intransitive verb). In the experiment, participants were instructed to read two sentences that formed a story, of which the second sentence was either a transitive or intransitive sentence. The participants then answered a related question about general knowledge, and their response times were measured. The results show that, whereas the mean response time in the ordinary intransitive condition was significantly longer than that in the ordinary transitive condition, the mean response time in the agent-implying intransitive condition was not significantly different from that of the corresponding transitive condition, suggesting that agent-implying intransitive verbs are interpreted as agentive. The findings suggest that agent-implying intransitive verbs instantly evoke agentivity, whereas ordinary intransitive verbs do not. The theoretical implications of the findings are discussed.
Solar Thermal Power Generation: Application of Internet of Things for Effective Control and Management

This chapter presents an overview of political, environmental, social, and technological risks associated with solar thermal power generation projects. The political risks are related to energy policies or treaties made governments adopt during a period and are country specific. Increasing government subsidies in renewable energy (RE) has a positive impact on RE projects since it encourages people to invest in RE projects, thereby having a positive impact on business. Internet of Things (IoT) can play a significant role in reducing uncertainties associated with solar thermal power generation, especially in dealing with technological risks. The IoT framework consists of the main controller, which communicates with each of the three blocks through two subcontrollers viz solar field (SF) controller and power block (PB) controller. The IoT model enables the system to predict direct normal irradiance (DNI) in a future time step based on real-time meteorological data.
THE STRUCTURAL AND FUNCTIONAL MODEL OF DESIGNING DIGITAL COMPETENCE OF FUTURE ELECTRICAL PROFILE SPECIALISTS

In the publication, the role of the design of the educational process in an agrotechnical institution of higher education is actualized. The author describes the theoretical and methodological aspects of developing the structural and functional model of designing the educational process on the example of digital competence of future specialists in electrotechnical engineering. The composed model generalizes theoretical results of designing the educational process in the form of interconnected components: target; methodological; subjective; objective; procedural; diagnostic-comparative. In particular: the target component consists in designing digital competence of future specialists of electrotechnical profile; the methodological component is implemented through the use of certain methodological approaches (competence, information, system, terminology, modeling); the subjective component unites teachers and students; the objective one is aimed at the components of the educational process; the procedural component determines the stages of the design activity; the diagnostic-comparative component is to determine the criteria, levels and indicators of digital competence of students.