Reviewerly/exHarmony huggingface dataset:
Translation of Collocations in Seasonal Letting Agreements: A Corpus-driven Study

In recent years, technology has entered the daily workflow of translators and (to a lesser extent) interpreters.In particular, language technologies have also shaped the discipline and provided a new paradigm for research.In this paper we will present a corpus-driven protocol to uncover collocational equivalents in legal genres, with special reference to seasonal letting agreements.In addition to the challenges posed by legal jargon, anisomorphisms, rhetorical conventions and so forth, collocations appear particularly problematic in the translation of legal texts.This paper will present corpora as an efficient and inexpensive means to uncover equivalents, find inspiration or help selecting among different options, reproduce the linguistic and cultural context of the target text, etc.
Transformer-based Detection of Multiword Expressions in Flower and Plant Names

Multiword expression (MWE) is a sequence of words which collectively present a meaning which is not derived from its individual words.MWEs detection is an important topic in different natural language processing (NLP) applications, including machine translation.Therefore, detecting MWEs in different domains is an important research topic.With this study, we explore state-of-the-art neural transformers in the task of detecting MWEs in flower and plant names.We evaluate different transformer models on a dataset created from Encyclopedia of Plants and Flower.We empirically show that neural transformers could outperform previous neural models like long-short term memory (LSTM) even in specific domains such as flower and plant names.
Use of Blockchain to Improve Case Studies in Food Supply

The current food supply is a linear economic model that directly or indirectly fulfills needs. However, this model has several weaknesses, such as the relationship between members of the supply chain or the lack of information to consumers about the origin of the product. In this paper we propose a new supply chain model via blockchain. This new model enables the concept of a circular economy and removes many of the disadvantages of the current supply chain. To coordinate all the transactions that occur in the food supply, a multi-agent system is created for this paper.
PERSEPSI SISWA TERHADAP MEDIA PEMBELAJARAN DALAM JARINGAN (Daring) PADA MATA PELAJARAN BIOLOGI DI MADRASAH ALIYAH NEGERI TARAKAN

Abstract: This study aims to look at students' perceptions of online learning media in Biology subjects at MAN Tarakan. This type of research is a survey research with a qualitative descriptive method. The population in this study was 200 students with a total sample of 66 students. Overall data was obtained based on scores and answers from student perception questionnaires distributed online via Google form. The results showed that students' perceptions of the use of learning media in the network system (Online) in Biology subjects at MAN Tarakan students had good perceptions of the platform as learning media in the network system (Online) in Biology subjects. Keywords: Perception, Media, Online.
Strengthening Connections Within GRSS [President’s Message]

I believe the past year has been a very important and transformative one for the IEEE Geoscience and Remote Sensing Society (GRSS). The Society continues to expand its influence in several ways, including Society initiatives, membership growth, journal submissions, and outreach. But perhaps the most important transformation has been the many in-person events we have been able to have in 2022 compared with the previous year. Hence, “Connections” is a theme for this column.
Metaverse: Exploring new areas for inter-Korean communication

Today, the concept of ‘Metaverse’ is emerging as a ‘virtual coexistence world’. The metaverse is receiving social attention as an alternative space to the real world and is being widely applied in everyday life. However, unlike in the economic and social fields, policies that utilize the potential of the digital virtual world realized by Metaverse in diplomatic terms are still limited. As an alternative to overcome the limitations of traditional diplomatic methods, we need to review the metaverse so that it can be used more actively. In other words, it is necessary to discuss the potential and scope of use of metaverse-based diplomacy as an approach that overcomes the limitations of limited reality and discovers new areas of possibility, not simply as an auxiliary means of traditional diplomacy. In particular, it is good to actively seek the possibility of application in issues with high geopolitical uncertainty and wide-ranging international sanctions, such as the issue of inter-Korean cooperation. The metaverse world provides a clue to overcome some of these realistic limitations. This is because, in the metaverse space, where non-face-to-face and two-way communication is possible, the burden of complex pre-requisites for direct exchange can be reduced, and topics for culture, knowledge, and friendship can be made widely through various actors not only in the government but also in the private sector. Exploring the inter-Korean non-face-to-face exchange space can be said to be a practical task for realizing metaverse diplomacy from our point of view.
Application of Data Mining for Visit Prediction at Amikom Creative Economy Park

A creative economy park is a place designed with strategic goals for technology skills collaboration, information and knowledge transfer, creation of innovative high-tech enterprises and entrepreneurs, introduction of new technology industries in creative economy enterprises to promote economic development. Yogyakarta Amikom University has been declared a Creative Economy Park and is known as Amikom Creative Economy Park (ACEP). ACEP includes multiple multimedia environments for targeting businesses such as software development, film, television, games, radio, animation, advertising, investment consulting, and project design. Every year, the number of institutions visiting Amikom Yogyakarta University carries the slogan Amikom Creative Economy Park with a fairly busy program of visits. The agenda for accepting this visit was carried out by Amikom's Public Relations Department (DKUI, Directorate of Public Relations and International Affairs). The evolution of visitor numbers from year to year, forecasts must be made to support the planning and preparation process when receiving visits. This research will discuss the trend of visitors having a comparative study in Amikom Creative Economy Park in the future. The data used in this study is visitor data from January 2019 to December 2019. This predictive data analysis uses the Autoregressive Integrated Moving Average (ARIMA) method and Exponential Smoothing as a comparison for the accuracy of the prediction. With the forecast of this visit, the planning and preparation for the Directorate of Public Relations and International Affairs and for the University AMIKOM Yogyakarta is to be done.
Educational Data Mining (EDM) Prediction of Student Study Period with Naïve Bayes Classifier and C4.5 Algorithm Comparison

Until now, many colleges are running to improve the quality of education to create a competitive environment. The wealth of data contained in the college can be put to good use according to the needs and processed into useful information to find out the relationship between the attributes of the data contained in it for analysis and the expected result in the form study achievements are related to study time, i.e. in adequate or late in the probable study period can be classified. Data mining, which refers to the analysis of data in the field of educational institutions, is also known as educational data mining (EDM). In the study conducted using two models of Naive Bayes Classifier i.e. Algorithms and C 4.5. The value of best accuracy in the Naive Bayes Classifier (NBC) algorithm model was 86.83% with a ratio of 80% training data, while in the model algorithm C 4.5 was 88.10% with a ratio of 90% training data. The application of EDM is expected to be maximized and developed so that it can contribute to the world of education and advance, especially in the field of data mining.
Learn Number Lines with Interactive Video Learning Media

This research is motivated by the difficulties of the teacher in implementing online learning, which makes students less enthusiastic and less able to understand the material in online learning, so the development of interactive video media is needed. This study aims to produce interactive video media for grade three elementary school number line materials tested for validity. The development model used in this study is the ADDIE model. The subjects in this study consisted of 1 teacher and four dose experts who were experts in their fields as media experts and material experts, and 12 students consisting of 3 people as individual tests and nine students as small group tests. The method of data collection in this study is the method of questionnaires and interviews. The data generated in this study are qualitative and quantitative. The data obtained were then analyzed using the mean formula to determine the average validation of interactive video media. The development of interactive video media was declared valid based on the assessments of media experts, design experts, material experts, individual test students, and small group students with an average range of 4.01 &lt; X 5, with the qualification "very good.” Thus, it can be indicated that the interactive video product is declared valid and suitable for use in learning, especially on the number line material for third grade of elementary school.
PENGEMBANGAN KOMIK DIGITAL BERBASIS PLATFROM (INSTAGRAM) PADA MATERI SISTEM EKSKRESI MANUSIA UNTUK SISWA KELAS VIII PUTRA SMP IT IBNU ABBAS TARAKAN

AbstrakPenelitian ini bertujuan untuk menghasilkan Komik Digital berbasis Platform (Instagram) pada materi sistem ekskresi manusia untuk siswa kelas VIII Putra SMP IT Ibnu Abbas Tarakan yang berkualitas dan untuk mengetahui respon siswa kelas VIII Putra SMP IT Ibnu Abbas Tarakan terhadap Komik Digital berbasis Platform (Instagram) pada materi sistem ekskresi manusia. Jenis penelitian ini adalah penelitian dan pengembangan (Reseach and Develoment) dengan menggunakan model ADDIE (Analysis, Design, Development, Implementation, Evaluation). Subjek uji coba dalam penelitian ini yaitu siswa kelas VIII Putra SMP IT Ibnu Abbas Tarakan yang berjumlah 23 Siswa. Keseluruhan data diperoleh berdasarkan skor dari angket penilaian ahli media, ahli materi, praktisi dan angket respon siswa. Hasil penelitian menunjukkan bahwa kualitas komik digital berbasis platform (instagram) pada materi sistem ekskresi manusia berdasarkan penilaian ahli media memperoleh hasil rata-rata skor (X) sebesar 3,6 (kategori sangat baik), penilaian ahli materi memperoleh hasil rata-rata skor (X) sebesar 3,4 (kategori sangat baik), penilaian praktisi memperoleh hasil rata-rata skor (X) sebesar 3,5 (kategori sangat baik) dan respon siswa berdasarkan hasil uji coba menunjukkan rata-rata skor (X) sebesar 3,6 (kategori sangat baik) pada uji coba kelompok kecil maupun uji coba kelompok besar. Kata Kunci: Komik Digital, Platform (Instagram), Sistem Ekskresi Manusia. AbstractThis research aimed to produce the quality Instagram-based Digital Comics related to human excretory system materials for Grade VIII male students of SMP IT Ibnu Abbas Tarakan and figure out the responses of Grade VIII male students of SMP IT Ibnu Abbas Tarakan to the Instagram-based Digital Comics related to human excretory system. The study was classified into R D (Research and Development) using the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. The tested subjects in this research were 23 male students of Grade VIII SMP IT Ibnu Abbas Tarakan. All collected data were based on scores from the questionnaires assessed by media experts, material experts, practitioners, and those from the students’ responses. The results show that the quality Instagram-based digital comics related to the human excretory system materials respectively assessed by the media expert had an average score (X) of 3,6 (very good category), by the material expert had an average score (X) of 3,4 (very good category), by practitioner had an average score (X) of 3,5 (very good category), and based on students’ responses had an average score (X) of 3,6 (very good category) in both small and large group trials.Keywords: Digital Comics, Instagram, Human Excretory System
Discovery Learning in E-Book with Natural Science Lesson at Elementary School

This research was motivated by problems in the media and learning models that were less innovative and varied during the online learning process, so it impacted students' lack of understanding, especially on the content of science lessons. This study aims to develop an e-book based on discovery learning for elementary science lessons. The subjects in this study were content experts, instructional design experts, learning media experts, and fifth-grade elementary school students. This research is development research by applying the ADDIE model. Data collection in this study was done by using a questionnaire method with quantitative descriptive analysis techniques. Based on the results of data analysis, the following results were obtained: 1) content experts 95.00%, 2) instructional design experts 93.75%, 3) learning media experts 87.50%, 4) individual trial results 83.33%, 5) small group trial results 90.50%. Thus the conclusions in this study indicate that this e-book based on discovery learning is in very good qualification and is suitable for use in science learning for fifth-grade elementary school.
PENERAPAN METODE PROTOTYPE DALAM PERANCANGAN BIMBINGAN MASYARAKAT PADA KEMENTRIAN AGAMA SATUAN KERJA OGAN ILIR

The Islamic Community Guidance at the Ministry of Religion is tasked with providing services, technical guidance, data and information management, as well as planning and reporting in the field of Islamic religious affairs and sharia development, building religious affairs offices and sakinah families, as well as Islamic religious information. dissatisfied with BIMAS services because registering for services alone can take a long time because it is still done manually, BIMAS data archiving is still archived in the ledger and BIMAS information giving must call or send messages to participants one by one. These constraints are deemed less effective in the implementation of BIMAS services. The method used is the Prototype method by using system development tools such as DFD and ERD. In designing the BIMAS information system, it aims to facilitate the community in providing services such as technical guidance services, marriage guidance and MTQ competitions.
Forecasting the Amount of Blood Storage Using the Support Vector Machine (Svm) Method

Blood transfusion is a process of sending or transferring blood to another place and the task is delegated to the PMI Blood Donation Unit with several tasks including; deployment and preservation of blood donors, provision and processing of blood, and distribution of blood to health agencies. However, the supply and demand from health agencies have a significant difference. The difference for each blood group is very large, in group O deficiency by 28%, in group A deficiency by 38%, in group B excess by 28%, and in group AB deficiency by 84%. To overcome this problem, it is necessary to estimate the demand for blood that will occur in the future period. One of the tools that can answer this problem is demand forecasting and what will be used in this study is forecasting using the Support Vector Machine (SVM) method. This SVM method is a relatively new machine learning-based technique for making predictions, both used in classification and regression cases. The result of this study obtained good MAPE values, namely in blood group O is 14%, in blood group A is 15%, in blood group B is 13%, and in blood type AB is 24%.
Leveraging Continuous Prompt for Few-Shot Named Entity Recognition in Electric Power Domain with Meta-Learning

ABSTRACT Conventional named entity recognition methods usually assume that the model can be trained with sufficient annotated data to obtain good recognition results. However, in Chinese named entity recognition in the electric power domain, existing methods still face the challenges of lack of annotated data and new entities of unseen types. To address these challenges, this paper proposes a meta-learning-based continuous cue adjustment method. A generative pre-trained language model is used so that it does not change its own model structure when dealing with new entity types. To guide the pre-trained model to make full use of its own latent knowledge, a vector of learnable parameters is set as a cue to compensate for the lack of training data. In order to further improve the model's few-shot learning capability, a meta-learning strategy is used to train the model. Experimental results show that the proposed approach achieves the best results in a few-shot electric Chinese power named entity recognition dataset compared to several traditional named entity approaches.
Three Heads Better than One: Pure Entity, Relation Label and Adversarial Training for Cross-domain Few-shot Relation Extraction

Abstract In this paper, we study cross-domain relation extraction. Since new data mapping to feature spaces always differs from the previously seen data due to a domain shift, few-shot relation extraction often perform poorly. To solve the problems caused by cross-domain, we propose a method for combining the pure entity, relation labels and adversarial (PERLA). We first use entities and complete sentences for separate encoding to obtain context-independent entity features. Then, we combine relation labels which are useful for relation extraction to mitigate context noise. We combine adversarial to reduce the noise caused by cross-domain. We conducted experiments on the publicly available cross-domain relation extraction dataset Fewrel 2.0[1]①, and the results show that our approach improves accuracy and has better transferability for better adaptation to cross-domain tasks.
Learner Guide

Written by a team of experienced teachers of Spanish, this textbook is designed to lead the adult beginner to a comprehensive knowledge of Spanish, giving balanced attention to the four key language skills (speaking, listening, reading and writing). It puts language learning into its real-life context, by incorporating authentic materials such as newspaper articles, poems and songs. It contains a learner and a teacher guide and is intended to complement study both inside and outside the classroom, by providing pair and group activities, as well as materials for independent learning. It also includes helpful reference features, such as a guide to grammatical terms, verb tables, vocabulary lists and a pronunciation guide. This extensively updated second edition features extra exercises to support the acquisition of good pronunciation, and is accompanied by a web companion that hosts expansion exercises, activities, solutions and useful links for each unit, as well transcripts, and access to brand new recordings of all the audio examples found in the book.
A Proposed Darknet Traffic Classification System Based on Max Voting Algorithms

The darknet refers to an anonymous address space on the Internet where people do not expect to interact with their computers so that it is considered malicious and provides them with a safe place where people can express themselves anonymously. Tools such as “tor" are also used in illegal activities such as disseminating child abuse, selling Drugs and Weapons, or distributing malicious software In addition to cyber-attacks. This proposed proposes a darknet traffic detection and classification system by using the Max Voting classifier Ensemble technique to produce the final predictions in a manner based on three algorithms: Random Forest and KNN and Gradient Boosting combined to get accurate results in case the client gets access to the internet using the darknet or not. As an expected contribution, the system will be got a higher Accuracy compared with the current systems, The proposed suggested working on a dataset of more than 100,465 records analyzed from the 2020 CIC-Dark collected from the Darknet.
Implementation of Robot Voice Interaction Functionality: PocketSphinx

We have already learned about the basic theory of speech recognition. In terms of concrete implementation, there are many mature packages for speech recognition available, the most closely integrated with ROS are the PocketSphinx speech recognition system and the Festival speech synthesis system. This chapter will introduce PocketSphinx in detail.
Analysis of the key points of library management and services in the new situation

The footsteps of information technology are constantly moving forward, and for various industries, the popularity of information technology brings both opportunities and challenges. In the environment of the information age, how libraries can sustain their development and progress is the primary issue for managers to consider now. As people have more and more free time, they come to the library to read more and more frequently, and as we use the library more and more, there are newer and higher demands for library management and services. This requires libraries to keep pace with the times, change the backward management and services, innovate the concept of management and services, the way and the details of them to meet the growing needs of people and provide better services for people to have a better reading experience.
Identifying Gaze Behavior Evolution via Temporal Fully-Weighted Scanpath Graphs

Eye-tracking technology has expanded our ability to quantitatively measure human perception. This rich data source has been widely used to characterize human behavior and cognition. However, eye-tracking analysis has been limited in its applicability, as contextualizing gaze to environmental artifacts is non-trivial. Moreover, the temporal evolution of gaze behavior through open-ended environments where learners are alternating between tasks often remains unclear. In this paper, we propose temporal fully-weighted scanpath graphs as a novel representation of gaze behavior and combine it with a clustering scheme to obtain high-level gaze summaries that can be mapped to cognitive tasks via network metrics and cluster mean graphs. In a case study with nurse simulation-based team training, our approach was able to explain changes in gaze behavior with respect to key events during the simulation. By identifying cognitive tasks via gaze behavior, learners' strategies can be evaluated to create online performance metrics and personalized feedback.