Reviewerly/exHarmony huggingface dataset:
Exploring terminological relations between multi-word terms in distributional semantic models

Abstract A term is a lexical unit with specialized meaning in a particular domain. Terms may be simple (STs) or multi-word (MWTs). The organization of terms gives a representation of the structure of domain knowledge, which is based on the relationships between the concepts of the domain. However, relations between MWTs are often underrepresented in terminology resources. This work aims to explore distributional semantic models for capturing terminological relations between multi-word terms through lexical substitution and analogy. The experiments show that the results of the analogy-based method are globally better than those of the one based on lexical substitution and that analogy is well suited to the acquisition of synonymy, antonymy, and hyponymy while lexical substitution performs best for hypernymy.
PENGARUH KECERDASAN EMOSIONAL TERHADAP PRESTASI BELAJAR PAI SISWA SMP DI JOMBANG

Emotional intelligence is a person's ability to recognize himself, control himself, motivate himself, empathize, and the ability to build relationships (cooperation) with others. Most teachers only consider students to excel if their intelligence scores are high, even though emotional intelligence influences success more. With good emotional intelligence, it is hoped that it can influence student achievement in PAI learning. The method used in this research is a quantitative survey method. With Linear Regression analysis technique. The sample of this research is the students of the one-roof SMPN Pengampon Kabuh Jombang with the results of the general simple linear regression equation: Y = a + bX. Y = 55.461 + 0.429X this equation can be translated: a constanta of 55.461 and a regression coefficient of X of 0.429 states that the regression coefficient is positive, so it can be said that the direction of the influence of variable X is positive. And seen from the r2 value of 0.472 or 47.2%, the amount of contribution (contribution) of intelligence to learning achievement in PAI and 52.8% is influenced by other factors.
Meaningful ICT integration into deprived rural communities’ multigrade classrooms

An innovation project’s key features for meaningful information and communication technologies (ICT) integration into multigrade classrooms of non-internet access and deprived rural communities are explored. Although the project implementation achievement differed in each school, the article focuses on the concurrent conditions that enabled ICT integration in some cases. The research evidence stems from open structured interviews in six multigrade primary schools and two regional workshops, and one selected lesson’s focused ethnography. Considering a wide-ranging ICT integration impediment review, it stands out the value of the Project’s lesson planning model that, in turn, has features suited to traditional student autonomy rooted in Mexican rural schools. The conclusion is that the synergy occurred amongst a minimum of equipment and digital resources, a planning model highlighting academic subject links, learning activities based on multi-modal resources, and the tradition of student autonomy. Even though the Project’s digital technologies are not cutting-edge, their innovative adaptation to multigrade schools in deprived communities is a pressing necessity in many countries.
Design of a Blockchain-based KRW Transfer System forSettlement and Distribution of Digital Content Copyright Fees

Recently, the growth of the digital content industry has led to complex rights relationships for creative works, resulting in unfair issues with copyright royalty settlements.To address these problems, various research efforts have been conducted using blockchain technology.However, the existing blockchain systems have limitations in actively integrating with external systems, making it difficult to guarantee the reliability of external data related to copyright royalty transfers.Therefore, this paper proposes a fiat currency transfer system that ensures the reliability of external data by scheduling transfer transactions and preventing duplicate execution of external systems, as well as enabling mutual verification of input/output information among participating nodes during the interaction process between blockchain and external systems.The proposed system improves performance and response speed by completing blockchain requests within a single transaction and ensures the consistency and reliability of external data by propagating the results to all participating nodes.
Design of Selective Hierarchical Cognitive Heart Wired Artificial Network

Artificial Intelligence Technology is playing an important role as the core engine of the future society.For building such a core engine, a highly efficient, structured and intelligent mechanism should be designed.As one of these directions, we proposed Hierarchical Cognitive Heart Wired Artificial Network which has Learning, Perception, Reasoning, Extraction and Selection function in a hierarchical frame.Especially in this system, emotional factors are designed to be combined with knowledge in the knowledge network.In the experiments, the proposed system was applied to event scheduling problem, the effects of emotional factors in the Emotion-Knowledge linkage structure were investigated.and the working phase of the functions is simulated.As a result, it shows that the effects of emotional factor on Decision making was traced.
A Study of Interaction Design for Improving the Usability of AI Service: Focused on HeyKakao and Naver Clova

In this paper, study on user experience to improve the usability of AI service platforms.There are natural language processing and technical problems that AI technology penetrates into life but cannot continue natural conversations.Accordingly, in order to examine the user experience, the user experience of Kakao's Hey Kakao and Naver's Clova application, which provide domestic AI complex services, was compared and analyzed.As a research method, a 1:1 face-to-face in-depth survey was conducted on men and women in their 20s and 40s who are familiar with VUI use, and user experience was analyzed by matching VUI usability category items such as efficiency, accuracy, flexibility, consistency, meaning, and AI usability evaluation.As a result, both applications had a different understanding of command recognition
See, Hear, and Learn to Describe--Crossmodal Information Processing Opens the Way to Smarter AI

At NTT Communication Science Laboratories, we are researching information processing across different types of media information such as images, sounds, and text.This is known as crossmodal information processing.The point of crossmodal information processing is to create a common space, which is a place where multiple types of media data are associated.The common space enables us to realize new functions that have never existed before: new transformations between different media-such as creating images and descriptions from sound-and the acquisition of concepts contained in media information.
Retracted: Monitoring and Sharing of Music Teaching Environment Resources Using Big Data Technology

[This retracts the article DOI: 10.1155/2022/3949443.].
Retracted: Heterogeneous Multi UAV Mission Planning Based on Ant Colony Algorithm Powered BP Neural Network

[This retracts the article DOI: 10.1155/2021/4369201.].
Analisis Peran Orang Tua dalam Pendampingan Kemampuan Membaca Anak Usia SD

This study aims to improve the reading ability of school students elementary school, where we all must have known that elementary school students class low, of course, not all of them can or are not fluent in reading, so they like it or not want parents to play an active role in children's education to improve abilities read their own children. But in reality there are still many parents who are busy with their respective jobs so that the activity of guiding children learning at home is not paid enough attention and there are also parents who do not understand their children's learning materials. The purpose of this research is to examine literature study regarding the effect of parental guidance on ability reading for low grade students. The data collection technique used was interviews with students' parents. The data analysis technique was carried out descriptively. The results of this study indicate parental guidance in reading ability their children can be seen from the way the parents make a schedule of learning activities at home well, create a pleasant atmosphere when guiding their children learning, by bringing in tutors when parents are less able to teach their children to read, giving them attention and always setting aside time to guide their children learn when their parents are busy working, and provide children with learning facilities and give them an award when their child's learning achievement increases, namely by giving applause, praise or you can give it a gift so that the child feels proud and becomes active for it Study. The conclusion of this study is parental guidance is good and right will have a good impact on children, in addition to needing guidance from teachers in children's schools also need guidance from their respective parents when at home.
Blockchain and the General Data Protection Regulation: Healthcare Data Processing

The General Data Protection Regulation (GDPR) of the European Union became binding in May 2018. The objective of the GDPR is essentially twofold. On the one hand, it seeks to facilitate the free movement of personal data between the various EU Member States, and, on the other hand, it establishes a framework for the protection of fundamental rights, based on the right to data protection as set out in Article 8 of the Charter of Fundamental Rights. The European Parliament has declared that the Blockchain must be considered a "tool that strengthens the autonomy of citizens by giving them the opportunity to control their data and decide which ones to share in the register, as well as the ability to choose who can see such data”, thus favoring the transparency of transactions. Blockchain (or distributed register technology – DLT) technologies and their potential for the European Union’s digital single market have been widely discussed in recent years. It has been argued that blockchain technologies could be a suitable tool to achieve some of the goals of GDPR. Blockchains can be designed to allow data sharing, and improve transparency on data access. This study analyzes the relationship between blockchain and GDPR, to highlight existing problems and study possible solutions in relation to the processing of health data.
Causas de bajas escolares de estudiantes de educación superior durante la pandemia COVID-19

This research focuses on leading causes analysis that originate school leaves from the Tecnológico Nacional de México (TecNM) San Luis Potosí campus during the COVID-19 pandemic January-June 2020 until the January-June 2022 semester and what the factors associated with them. It is a study with a quantitative approach, descriptive scope, and cross-sectional design. It analyzed the Database of the Integral Information System (SII) of the institution. The results indicated that the leading causes for which students definitively withdrawals from their studies were: 49% for failing and 51% for other reasons; the subjects that fail most frequently are: Integral Calculus; Differential Calculus; Linear Algebra; and Probability and Statistics, taught in the first three semesters of the different degree programs. The factors associated with the academic situation of the students are the average grade, the degree they study, and the number of semesters studied.
Six colours for inclusion: results of an explorative activity in a simplexity approach

Schools and teachers are called upon, in the age of complexity, to manage a plurality of problems related to the numerous stimuli arising from the personal and environmental influences of students. This implies that a new way of working in the direction of creativity is linked to a different way of using educational elements. This paper presents the results of an exploratory activity, conducted on 657 teachers in training at the University of Salerno, as part of the training activities to support the teaching of pupils with special educational needs. The aim was to investigate whether teachers in training can develop lateral thinking, based on suggestions derived from the studies of de Bono (2015) and, specifically, from his theory "Six Hats for Thinking", highlighting points of agreement with the theory of simplicity proposed by Berthoz ( 2011).
Robust Subgroup Multisignature with One-Time Public Keys in Order

Robust subgroup multisignature allows any subgroup of signers from a global set to sign a given message on behalf of the whole group, and the individual signatures should be verified before the combination process, which resists poison signature attacks. An emerging application of robust subgroup multisignatures in blockchain is that a qualified subgroup of a global set of users has reached agreement. In the integrated blockchain and edge computing system, the edge server can naturally act as a combiner in multisignatures and help other end devices produce the final aggregate signature. In this paper, we propose a robust subgroup multisignature with one-time public keys in order that has two advantages for solving the signers ordering problem and one-time public key problem simultaneously. Our scheme is a nontrivial extension of Galindo et al.’s robust subgroup multisignature scheme and can be proven unforgeable, robust and chronological in random oracles. Our scheme can also be suitable for the consortium blockchain by adding a noninteractive zero-knowledge (NIZK) proof system for certifying the one-time public keys.
"Data Protection in Organization by the Implementation of Cyber Security"

Cyber security safeguards data, networks, programmes, and other information from unauthorized or unsupervised access, destruction, or change. Because of various security concerns and cyber-attacks, cyber security is crucial in today’s environment.
Discriminating between optical coherent superposition states with imperfect detection

Quantum state discrimination between optical coherent superposition states is considered. The Helstrom bound for imperfect detection is evaluated. Under a physically realistic model of photodetection, we study several techniques for discriminating between optical coherent superposition states. We investigate quantum error probabilities for the Kennedy receiver, the Dolinar receiver and the unitary rotation scheme proposed by Sasaki and Hirota for sub-unity detector efficiency. Also, we study the feedback strategy employed by the Dolinar receiver to achieve the Helstrom bound for sub-unity detection efficiency.
Blockchain in Hospitality and Tourism: A Game-Changer for Asian Markets

Blockchain technology has gained significant attention in various industries, including the tourism and hospitality sector.This research article explores the current and potential use of blockchain in the hotel and tourism industry in Asian countries, highlighting its benefits and challenges.The study examines the advantages of blockchain technology, such as decentralization, auditability, persistency, and its various applications, including cryptocurrency, Internet of Things (IoT), financial services, and public services.The article also discusses the potential impact of blockchain technology on the Asian hospitality industry and its potential to revolutionize the way the industry operates.Finally, the study presents recommendations and future directions for the adoption and implementation of blockchain technology in the Asian tourism and hospitality sector.
The Extent of the Use of Community Policing in Curbing Kidnapping in Anambra State

The purpose of the study was to determine the extent of the use of community policing in curbing kidnapping in Anambra State.Two research questions and two hypotheses guided the study.The study employed a descriptive survey research design.The population for the study was 1,620 (450 executive and 1,170 nonexecutive) members of the vigilantee group in Anambra State.The sample size was 321 (90 executive and 231 non-executive) members of the vigilantee group in Anambra State and was arrived at using Taro Yamane sample size formula.Muit-stage sampling technique was used.The instrument for the study was 17 items sructured questionnaire of two clusters titled "Extent of the Use of Community Policing in Curbing Kidnapping Questionnaire" (EUCPCKQ).Using Cronbach Alpha, an overall reliability coefficient of 0.78 was obtained on the ICPCKQ instrument.Research questions were responded to using mean and standard deviation while the hypotheses were tested at 0.05 level of significance using t-test.It was found to an high extent, the vigilantee group has assisted in curbing kidnapping in Anambra State, Nigeria.The findings of the study also shows to an high extent, weed and seed has been used in curbing kidnapping in Anambra State, Nigeria.Based on the findings, The state government should recruit more vigilantees and also educate community members on the importance of weeding out the kidnappers and bad ones in the community.
Effectiveness of Learn English Vocabulary Application in Enriching Students’ Vocabulary Learning

This research was conducted using pre-experimental research to determine the effectiveness of Learn English Vocabulary application in enriching students’ vocabulary learning among the 7th-grade students of SMP Negeri 20 Pontianak. The total population was 186 students, and the sample was 15 students from class F. The data were gathered using a test in a form of multiple choices with a total of 25 questions. The test was distributed in a form of a pre-test and a post-test. The data were analysed using Microsoft Excel and SPSS v.26 with a 5% significance level. It showed that there was an enrichment of students’ vocabulary learning. It was indicated by the values of Sig. (2-tailed) score from the t-test calculation which was 0.000. It means the value was lower than 0.05. The hypothesis testing result also strongly provides evidence by the acceptance of the hypothesis alternative with a t score of 8.5 higher than the ttable score of 2.145. Moreover, the effect size calculation showed that the significant effect of the application is in a score of 2.1 which is interpreted as a strong effect. Therefore, the use of Learn English Vocabulary application is significantly effective in enriching students’ vocabulary learning.
Wildfire Perimeter Detection via Iterative Trimming Method

The perimeter of a wildfire is essential for prediction of the spread of a wildfire. Real-time information on an active wildfire can be obtained with Thermal InfraRed (TIR) data collected via aerial surveys or satellite imaging, but often lack the actual numerical parametrization of the wildfire perimeter. As such, additional image processing is needed to formulate closed polygons that provide the numerical parametrization of wildfire perimeters. Although a traditional image segmentation method (ISM) that relies on image gradient or image continuity can be used to process a TIR image, these methods may fail to accurately represent a perimeter or boundary of an object when pixels representing high infrared values are sparse and not connected. An ISM processed TIR image with sparse high infrared pixels often results in multiple disconnected sub-objects rather than a complete object. This paper solves the problem of detecting wildfire perimeters from TIR images in three distinct image processing steps. First, Delaunay triangulation is used to connect the sparse and disconnected high-value infrared pixels. Subsequently, a closed (convex) polygon is created by joining adjacent triangles. The final step consists of an iterative trimming method that removes redundant triangles to find the closed (non-convex) polygon that parametrizes the wildfire perimeter. The method is illustrated on a typical satellite TIR image of a wildfire, and the result is compared to those obtained by traditional ISMs. The illustration shows that the three image processing steps summarized in this paper yield an accurate result for representation of the wildfire perimeter.
Blockchain Design and Modelling

Ontology engineering, along with semantic Web technologies, allow the semantic development and modeling of the operational flow required for blockchain design. The semantic Web, in accordance with W3C, provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries, and can be seen as an integrator for various content, applications and information systems. The most widely used blockchain modelling system, by abstract representation, description and definition of structure, processes, information and resources, is the enterprises modelling. Enterprise modelling uses domain ontologies by model representation languages.
Heterogeneous Multi-Party Learning With Data-Driven Network Sampling

Multi-party learning provides an effective approach for training a machine learning model, e.g., deep neural networks (DNNs), over decentralized data by leveraging multiple decentralized computing devices, subjected to legal and practical constraints. Different parties, so-called local participants, usually provide heterogenous data in a decentralized mode, leading to non-IID data distributions across different local participants which pose a notorious challenge for multi-party learning. To address this challenge, we propose a novel heterogeneous differentiable sampling (HDS) framework. Inspired by the dropout strategy in DNNs, a data-driven network sampling strategy is devised in the HDS framework, with differentiable sampling rates which allow each local participant to extract from a common global model the optimal local model that best adapts to its own data properties so that the size of the local model can be significantly reduced to enable more efficient inference. Meanwhile, co-adaptation of the global model via learning such local models allows for achieving better learning performance under non-IID data distributions and speeds up the convergence of the global model. Experiments have demonstrated the superiority of the proposed method over several popular multi-party learning techniques in the multi-party settings with non-IID data distributions.
3D-Aware Adversarial Makeup Generation for Facial Privacy Protection

The privacy and security of face data on social media are facing unprecedented challenges as it is vulnerable to unauthorized access and identification. A common practice for solving this problem is to modify the original data so that it could be protected from being recognized by malicious face recognition (FR) systems. However, such “adversarial examples” obtained by existing methods usually suffer from low transferability and poor image quality, which severely limits the application of these methods in real-world scenarios. In this paper, we propose a 3D-Aware Adversarial Makeup Generation GAN (3DAM-GAN). which aims to improve the quality and transferability of synthetic makeup for identity information concealing. Specifically, a UV-based generator consisting of a novel Makeup Adjustment Module (MAM) and Makeup Transfer Module (MTM) is designed to render realistic and robust makeup with the aid of symmetric characteristics of human faces. Moreover, a makeup attack mechanism with an ensemble training strategy is proposed to boost the transferability of black-box models. Extensive experiment results on several benchmark datasets demonstrate that 3DAM-GAN could effectively protect faces against various FR models, including both publicly available state-of-the-art models and commercial face verification APIs, such as Face++, Baidu and Aliyun.