Reviewerly/exHarmony huggingface dataset:
i-Align: an interpretable knowledge graph alignment model

Abstract Knowledge graphs (KGs) are becoming essential resources for many downstream applications. However, their incompleteness may limit their potential. Thus, continuous curation is needed to mitigate this problem. One of the strategies to address this problem is KG alignment, i.e., forming a more complete KG by merging two or more KGs. This paper proposes i-Align, an interpretable KG alignment model. Unlike the existing KG alignment models, i-Align provides an explanation for each alignment prediction while maintaining high alignment performance. Experts can use the explanation to check the correctness of the alignment prediction. Thus, the high quality of a KG can be maintained during the curation process (e.g., the merging process of two KGs). To this end, a novel Transformer-based Graph Encoder (Trans-GE) is proposed as a key component of i-Align for aggregating information from entities’ neighbors (structures). Trans-GE uses Edge-gated Attention that combines the adjacency matrix and the self-attention matrix to learn a gating mechanism to control the information aggregation from the neighboring entities. It also uses historical embeddings , allowing Trans-GE to be trained over mini-batches, or smaller sub-graphs, to address the scalability issue when encoding a large KG. Another component of i-Align is a Transformer encoder for aggregating entities’ attributes. This way, i-Align can generate explanations in the form of a set of the most influential attributes/neighbors based on attention weights. Extensive experiments are conducted to show the power of i-Align. The experiments include several aspects, such as the model’s effectiveness for aligning KGs, the quality of the generated explanations, and its practicality for aligning large KGs. The results show the effectiveness of i-Align in these aspects.
UTILIZATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES BY THE FARMERS

Information and communication technologies (ICTs) can help farmers access the information they need. Nowadays, an array of ICTs tools and projects are available not only in urban areas but in rural areas also. However effective utilization of ICTs for accessing agricultural information by the farmers is the major concern as generally, people use them more for entertainment and time passing. To what extent the farmers are using the ICTs in accessing agriculture information is fundamental for redesigning the agricultural development projects integrating the ICTs. Keeping this in view, the study was undertaken to ascertain the extent of the use of ICTs for accessing agricultural information by the farmers of South Gujarat. The study was carried out in the Valsad and Navsari districts of Gujarat for 120 farmers. Multistage random sampling was adopted for the selection of respondents. An Ex-post-facto research design was used for the study. Results of the study indicated that the majority (62.50 percent) of the respondents had a moderate level of extent of utilization of ICTs followed by 19.17 and 18.33 percent of them had high and low extent of utilization, respectively. Out of the 14 factors studied, education, extension participation, training received, mass media exposure, information source accessibility, innovativeness, social participation, and economic motivation were found positively and highly significantly correlated with the extent of use of ICTs.
The Effectiveness of Using Advertisement to Improve Students’ Writing Skill

This research was conducted to analyze the effectiveness of using advertisements in improving students writing skills. The subject of this research was an English teacher and 26 students in X-MIPA class. To gather the data, the interview and questionnaire were conducted and the interview was done with the teacher the questionnaire was given to the students and then qualitatively analyzed. To analyze the data gotten, these steps were used; data reduction, data display, and conclusion. The study's conclusions showed that using advertisements in writing lessons helped students feel happy, enthusiastic, and motivated. However, some students had trouble expressing their thoughts in writing lessons due to a lack of vocabulary. The usage of advertisements in the classroom has helped students' writing abilities. Based on these findings, it is recommended that all teachers use advertising intensively in their teaching to further improve their students' writing skills.
On Deploying Quantum-Resistant Cybersecurity in Intelligent Infrastructures

As quantum-safe algorithms are increasingly implemented in security protocols used in current and emerging digital services, there is also a corresponding need to map the current state of security protocols and applications and their preparedness for the post-quantum era. In this paper, we review current security recommendations, existing security libraries, and the support of Post-Quantum Cryptography (PQC) in widely-used security protocols. We also present a practical assessment of recently selected PQC algorithms by the National Institute of Standards and Technologies (NIST) PQC standardization on typical platforms that can be deployed in intelligent infrastructures (e.g., smartphones and single-boards), and recently recommended hash-based signatures for software/firmware signing. Finally, we discuss how incoming post-quantum migration affects selected areas in intelligent infrastructures.
Who is Alyx? A new behavioral biometric dataset for user identification in XR

Introduction: This paper addresses the need for reliable user identification in Extended Reality (XR), focusing on the scarcity of public datasets in this area. Methods: We present a new dataset collected from 71 users who played the game “Half-Life: Alyx” on an HTC Vive Pro for 45 min across two separate sessions. The dataset includes motion and eye-tracking data, along with physiological data from a subset of 31 users. Benchmark performance is established using two state-of-the-art deep learning architectures, Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU). Results: The best model achieved a mean accuracy of 95% for user identification within 2 min when trained on the first session and tested on the second. Discussion: The dataset is freely available and serves as a resource for future research in XR user identification, thereby addressing a significant gap in the field. Its release aims to facilitate advancements in user identification methods and promote reproducibility in XR research.
Evaluating Factual Consistency of Texts with Semantic Role Labeling

Automated evaluation of text generation systems has recently seen increasing attention, particularly checking whether generated text stays truthful to input sources.Existing methods frequently rely on an evaluation using taskspecific language models, which in turn allows for little interpretability of generated scores.We introduce SRLScore, a reference-free evaluation metric designed with text summarization in mind.Our approach generates fact tuples constructed from Semantic Role Labels, applied to both input and summary texts.A final factuality score is computed by an adjustable scoring mechanism, which allows for easy adaption of the method across domains.Correlation with human judgments on English summarization datasets shows that SRLScore is competitive with state-of-the-art methods and exhibits stable generalization across datasets without requiring further training or hyperparameter tuning.We experiment with an optional co-reference resolution step, but find that the performance boost is mostly outweighed by the additional compute required.Our metric is available online at:
Rigorous modeling of a confocal microscope

A reliable tool for simulations of confocal microscopes shall be developed to enable improved model-based dimensional metrology. To simulate measurements on rough surfaces the boundary element method (BEM) simulation tool <i>SpeckleSim</i>, developed by the <i>ITO</i> of the University of Stuttgart, is combined with a Fourier optics based image formation. <i>SpeckleSim</i>, which calculates the light-structure interaction by solving the Maxwell equations, is compared with the well-known FEM based solver <i>JCMsuite</i> and the FDTD based solver <i>Ansys Lumerical</i>. As an example, a rectangular shaped line is used as an object. Due to different boundary conditions the results show as expected small deviations, which require further investigations. First comparison results and the general concept of the image formation method will be presented.
An Impact of Explicit Teaching of Reading Strategies on the Reading Motivation of Pakistani ESL Learners

Researchers advise teachers to help students develop a passion for reading to enhance their reading abilities. This action research aims to ascertain the effect of explicit teaching of reading strategies on Pakistani undergraduate ESL learners. The students received explicit reading strategy instruction over a four-month period in two cycles. The data was gathered with the help of a questionnaire i.e. Motivation for Reading Questionnaire (MRQ) before and after the intervention stage. The findings show that teaching reading strategies explicitly ensures a positive impact on students’ motivation to read. As a result, it is discovered that students can get motivated to read if they are familiar with reading strategies, but what is the primary step to create initially is an interactive and interesting environment in the classroom. This study is important for language educators and teacher educators who want to motivate students. It additionally reinforces the usefulness of various existing reading strategies for motivating learners at a Pakistani private institution.
ANALISIS KESULITAN BELAJAR PESERTA DIDIK DENGAN KEMAMPUAN LITERASI RENDAH (Studi kasus kesulitan belajar akademik di kelas V SDN Cibaregbeg Semester Gasal Tahun Ajaran 2021/2022)

This research uses case study research with a qualitative approach. The purpose of this study was to determine the learning difficulties of students with low literacy skills at SDN Cibaregbeg, Sukabumi Regency in 2021/2022. The subject studied in this study was one of the students in the fifth grade at SDN Cibaregbeg, Sukabumi Regency. Data collection and data recording were carried out through procedures such as observation, interviews, and documentation. The data analysis technique used in this study is the data reduction, data presentation, and verification (conclusion) stages. To obtain the results of the study which looked at the learning difficulties of students with low literacy skills at SDN Cibaregbeg, the researchers used credibility, transferability, dependability, and confirmability tests which showed that the factors causing learning difficulties in students with low literacy skills were internal and external factors. Students do not have good learning motivation and have low interest in reading so that students experience learning difficulties, especially in learning to read. Efforts that can be made to deal with the problem of learning difficulties is to encourage students to study regularly both at home and at school. Another thing that can be done is to motivate students not to forget the benefits of learning by providing interesting learning.
Secure Information Sharing for the Supply Chain Using Blockchain Technology

Blockchain is a surface new virtual age that allows ubiquitous economic transactions between dispersed untrustworthy without the need for intermediaries such as banks. This paper investigates the impacts of the blockchain age on the food delivery network and agribusiness, presents a list of currently ongoing initiatives and activities, and considers general consequences, challenging conditions, and possibilities, with an emphasis on the development of those activities. Our findings indicate that blockchain is a potential age closer to evident Numerous ongoing projects addressing various food-related challenges are focusing on the food supply chain. and products, but numerous obstacles and problems still stand in the way of its mainstream acceptance among farmers and agricultural systems. Rules, regulations, technical components, and education are all part of these tough situations.
Rethinking Reading at Home: Connecting families with multilingual digital texts

Reporting a Brisbane Catholic Education (BCE) project spanning 2018-2020, this paper looks at what happened when early primary, multilingual students were given e-readers with bilingual texts to take home to read together with their families. The shift in pedagogy to view our learners as multilingual, from learning English to developing multicompetence, influenced our decision to make digital texts in community languages more readily available to our students. Although our increasingly digital world has led to improved access to information, texts in different languages and the opportunity for students to access learning in different ways, we realised that students at school, particularly those from a refugee background, have limited access to these resources.&#x0D; Along with improved access for students, we also wanted parents to have access to reading materials in their home languages, so that they could read together with their young children. Our goal was not only to facilitate reading in both home languages and English but to create greater student engagement in reading, while strengthening home and English literacy. In the course of compiling the digital library, we realised that we needed to find out more about what helps our multilingual students with reading and gain a greater understanding of family literacy practices in our school communities. Our learnings about the sustainability of libraries, student progress in reading, and family literacy practices in Brisbane Catholic Education school communities has important implications for how we teach multilingual learners to read today
Possibilities and Limitations of electronic criminal proceedings in the Introduction of Legal Tech

When The Act on the Use of Electronic Document in Criminal Justice Procedures is fully implemented in 2024, it is expected that full-fledged electronic litigation will be possible in criminal procedures. The scope of application of The Act on the Use of Electronic Document in Criminal Justice Procedures is limited to criminal justice affairs, but in the long run, it will expand to the macroscopic perspective of digitalization and intelligent informatization of overall criminal justice services. However, even if the law or system is established, there may be various expected problems in the process of operation. To this end, in this paper, first of all, the obstacles to the activation of Legal Tech, which is the environmental basis of electronic criminal proceedings, were examined. After confirming the specific aspects of the litigation, we examined the points where the electronic criminal proceedings can function or expand in the trial process In this paper, first of all, the fundamental cause of the lack of discussion on Legal Tech, which can be the environmental basis of electronic criminal proceedings, was identified. While accepting legal tech, such as intelligent information technology, the author raised issues such as our still conservative legal system and practices, information accessibility of personal information, and intellectual property rights infringement. Next, as a supplementary point for the success of electronic criminal proceedings, a plan to resolve the reluctance of those involved in the case in electronic criminal proceedings and a plan to prevent abuse of accumulated data were presented. Next, in the introduction process by stage of litigation, it was ordered to improve the system considering the difference in digital literacy in the process of submitting litigation documents, the issue of equality in the process of distributing electronic documents, and legislative overhaul for exceptions to the provision of service. On the other hand, the implementation of the Criminal Procedure Electronic Documents Act provides significant implications for e-discovery. In the disclosure of evidence, the practice of written caution will be overcome, and various problems raised in the academic world in relation to the refusal of the investigation agency to disclose evidence will be resolved. It will be possible to examine the adequacy of the reason for refusal by the investigative agency, and in particular, it will be possible to secure the binding force of the court's order to disclose evidence and prepare a separate regulation so that the investigative agency cannot refuse the order to disclose evidence. In addition, in this paper, we also looked at the possibility of using intelligent information technology in determining the verifiable power or reliability of electronic remote statements and statements that can be used in courts.
False Information Detection Based on Multimodal Attention Detection Network

With the development of the Internet, the distance between people is getting closer and closer under the bridge of the Internet. Especially the emergence of social software and media networks such as Weibo, Twitter, etc., has truly realized that “scholars do not go out and know everything about the World”. However, this also provides a way for criminals to spread false information. False information mostly appears on the Internet in the form of a combination of pictures and texts, which makes it very difficult to detect and identify false information. The current mainstream multi-modal false information detection methods do not consider the relationship between different modal features, and more only use simple feature splicing to detect and discriminate false information, and the detection effect is very poor. Aiming at this problem, this paper proposes a multimodal false information detection method based on attention mechanism. After extracting the feature vectors of the visual and language modalities, the attention mechanism is used to realize the interaction between different modal features, and the model construction is completed through feature fusion. Finally, the detection of false information is realized. Compared with the current mainstream methods, the model proposed in this paper has achieved an excellent improvement, with an improvement of more than 6% in terms of accuracy.
Generating Video Game Scripts with Style

While modern language models can generate a scripted scene in the format of a play, movie, or video game cutscene the quality of machine generated text remains behind that of human authors.In this work, we focus on one aspect of this quality gap; generating text in the style of an arbitrary and unseen character.We propose the Style Adaptive Semiparametric Scriptwriter (SASS) which leverages an adaptive weighted style memory to generate dialog lines in accordance with a character's speaking patterns.Using the LIGHT dataset as well as a new corpus of scripts from twenty-three AAA video games, we show that SASS not only outperforms similar models but in some cases can also be used in conjunction with them to yield further improvement.
Toward Consistent and Informative Event-Event Temporal Relation Extraction

Event-event temporal relation extraction aims to extract the temporal order between a pair of event mentions, which is usually used to construct temporal event graphs.However, event graphs generated by existing methods are usually globally inconsistent (event graphs containing cycles), semantically irrelevant (two unrelated events having temporal links), and context unaware (neglecting neighborhood information of an event node).In this paper, we propose a novel event-event temporal relation extraction method to address these limitations.Our model combines a pretrained language model and a graph neural network to output event embeddings, which captures the contextual information of event graphs.Moreover, to achieve global consistency and semantic relevance, (1) event temporal order should be in accordance with the norm of their embeddings, and (2) two events have temporal relation only if their embeddings are close enough.Experimental results on a real-world event dataset demonstrate that our method achieves state-of-the-art performance and generates high-quality event graphs.
User Simulator Assisted Open-ended Conversational Recommendation System

Conversational recommendation systems (CRS) have gained popularity in e-commerce as they can recommend items during user interactions.However, current open-ended CRS have limited recommendation performance due to their short-sighted training process, which only predicts one utterance at a time without considering its future impact.To address this, we propose a User Simulator (US) that communicates with the CRS using natural language based on given user preferences, enabling long-term reinforcement learning.We also introduce a framework that uses reinforcement learning (RL) with two novel rewards, i.e., recommendation and conversation rewards, to train the CRS.This approach considers the long-term goals and improves both the conversation and recommendation performance of the CRS.Our experiments show that our proposed framework improves the recall of recommendations by almost 100%.Moreover, human evaluation demonstrates the superiority of our framework in enhancing the informativeness of generated utterances. 1
Sentimental Matters - Predicting Literary Quality by Sentiment Analysis and Stylometric Features

The task of predicting reader appreciation or literary quality has been the object of several studies.It remains, however, a challenging problem in quantitative literary analyses and computational linguistics alike, as its definition can vary a lot depending on the genre of literary texts considered, the features adopted, and the annotation system employed.This paper attempts to evaluate the impact on reader appreciation, defined as online users' ratings, of sentiment range and sentiment arc patterns versus traditional stylometric features.We run our experiments on a corpus of English-language literary fiction, showing that stylometric features alone are helpful in modelling literary quality, but can be outperformed by analysing the novels' sentimental profile.