Reviewerly/exHarmony huggingface dataset:
Named Entity Recognition in the Romanian Legal Domain

Recognition of named entities present in text is an important step towards information extraction and natural language understanding. This work presents a named entity recognition system for the Romanian legal domain. The system makes use of the gold annotated LegalNERo corpus. Furthermore, the system combines multiple distributional representations of words, including word embeddings trained on a large legal domain corpus. All the resources, including the corpus, model and word embeddings are open sourced. Finally, the best system is available for direct usage in the RELATE platform.
Identifikasi Chatbot dalam Meningkatkan Pelayanan Online Menggunakan Metode Natural Language Processing

Chatbot is a software with artificial intelligence that can imitate human conversations through text messages or voice messages. This chatbot can convey information, according to the knowledge that has been given previously. Helping the limitations of the academic section in answering questions posed by students. The method in this study was sourced from a questionnaire distributed to students at the Muhammadiyah University of West Sumatra. Based on the analysis of the questionnaire, there are 40 questions that are often asked by students to the academic section. Then it is processed using Natural Language Processing (NLP). Natural Language Processing is a branch of science from artificial intelligence that is able to study communication between humans and computers through natural language. The processing stage is to identify the intent, process the input and display the results according to the input. The results of the test using a questionnaire addressed to 227 students got a score of 3,55 with a very good predicate. Then do the test using 40 question and answer data. So, obtained 37 appropriate answers and 3 answers that are not in accordance with the percentage of answer accuracy generated from the chatbot is 92.5 percent. The results of this test have been able to respond to the questions asked by students. This chatbot can make it easier for students to get information with a very good level of accuracy
Analyzing Grammatical Errors Committed by Students in Writing in the Academic Year 2020/2021

This study aimed to analyze the types of errors in writing recount texts and identify the source of errors in students. The subjects of this study were tenth-grade students of Languages major ??at SMA Negeri 1 Kuta Selatan with a total of 31 students. This research was qualitative descriptive research. Data were collected from students' writing assignments, questionnaires, and interviews. This study used the theory of Dulay et al. (1982) to find out the types of errors supported with the theory from Sawalmeh (2013) regarding spelling errors which was supported by the theory from Besten &amp; Granger (2011). The theory from Brown (2007) was used to find out the source of students' errors. The results of this study indicate that the types of errors found in student texts are omission, misformation, addition, misordering, and spelling. Sources of student errors are interlingual transfer, intralingual transfer, the context of learning, and communication strategy.
A Semantic Filter Based on Relations for Knowledge Graph Completion

Knowledge graph embedding, representing entities and relations in the knowledge graphs with high-dimensional vectors, has made significant progress in link prediction.More researchers have explored the representational capabilities of models in recent years.That is, they investigate better representational models to fit symmetry/antisymmetry and combination relationships.The current embedding models are more inclined to utilize the identical vector for the same entity in various triples to measure the matching performance.The observation that measuring the rationality of specific triples means comparing the matching degree of the specific attributes associated with the relations is well-known.Inspired by this fact, this paper designs Semantic Filter Based on Relations(SFBR) to extract the required attributes of the entities.Then the rationality of triples is compared under these extracted attributes through the traditional embedding models.The semantic filter module can be added to most geometric and tensor decomposition models with minimal additional memory.Experiments on the benchmark datasets show that the semantic filter based on relations can suppress the impact of other attribute dimensions and improve link prediction performance.The tensor decomposition models with SFBR have achieved state-of-the-art.
Factors affecting can Tho university’s brand value - approach from students

The study aims to identify factors influencing the brand value of Can Tho University. Research data were collected from 340 students studying at Can Tho University. By applying the exploratory factor analysis (EFA) and multivariate linear regression, the study has indicated factors putting positive impacts on Can Tho University's brand value. They are the university's reputation, training quality, graduate prospects, and alumni. In which, the training quality has the strongest influence on the brand value of the university.
Metode K-Means Untuk Pemetaan Persebaran Usaha Mikro Kecil Dan Menengah

Developments in the current era of globalization are very dependent on the economic sector which is the benchmark of success carried out by the government. The role of the community in national development in the economic field is the existence of Micro, Small and Medium Enterprises (MSMEs). To increase the role of MSMEs as a benchmark for the success of the economic sector, there must be support from the government, such as assistance for business owners with limited costs. The purpose of this study is to determine community business groups as a measure of the level of business, making it easier for the government to provide assistance. The K-Means Clustering method is a method used for grouping business levels based on the income that exists in today's society. The result of this research is a website-based business-level grouping system used by the Cooperatives and SMEs Office by grouping them into micro, small and medium-sized businesses based on income/assets.
Threatening trends in the use of bot pharms to the detrimation of the state interests of Ukraine: prevention and control mechanisms

The concepts and types of bots are considered. The signs and spheres of activity of bot farms are determined. The algorithm for creating and distributing fake pages is outlined. Procedures for responding to the dissemination of false and unreliable information within the current legislation of Ukraine are detailed. The achievements of the domestic special services in the direction of counteracting the illegal activities of bot farms, which are coordinated by curators from the Russian Federation, are highlighted. The task of pro-Russian bot farms in Ukraine is generalized. The principles of the state policy of combating fakes and propaganda on social networks are determined. The directions of improvements of the organizational and legal framework for the systematic counteraction to the functioning of crime bot farms as a threat to the state interests of Ukraine are specified.
Impact of Knowledge Management Practices on Job Satisfaction and Employee Retention in Banking and IT Industries in Sri Lanka

Knowledge has become a fundamental asset whose successful application helps organizations to remain competitive while delivering creative products and services. Knowledge intensive firms are organizations that employ highly qualified professionals as the majority and the employees in these organizations are mainly engaged in knowledge intensive activities. IT and Banking industries have been identified as knowledge intensive industries following these conditions and they have been implementing different practices to manage knowledge. However, IT and banking industries are experiencing a high turnover rate. This study aims to identify how the use of knowledge management practices contributes towards employee retention in IT and banking industries. Quantitative approach was used for the research. The sample size was 179, comprising of 97 from IT industry and 82 from banking industry. The data was gathered using a structured questionnaire. There is a strong positive relationship between knowledge management practices and employee satisfaction and employee intention of retention. The study showed that the adoption of knowledge management practices in IT industry is higher than the banking industry. It found that the impact of knowledge management practices on employee retention is slightly higher in IT industry than banking industry. This concludes that, the impact of knowledge management practices on employee retention depends on the industry and retention is high when the adoption of knowledge management practices is high. The results give insights to policy makers and managers of IT and banking industries in developing knowledge management practices.
Identifying the Importance of Content Overlap for Better Cross-lingual Embedding Mappings

In this work, we analyze the performance and properties of cross-lingual word embedding models created by mapping-based alignment methods.We use several measures of corpus and embedding similarity to predict BLI scores of cross-lingual embedding mappings over three types of corpora, three embedding methods and 55 language pairs.Our experimental results corroborate that instead of mere size, the amount of common content in the training corpora is essential.This phenomenon manifests in that i) despite of the smaller corpus sizes, using only the comparable parts of Wikipedia for training the monolingual embedding spaces to be mapped is often more efficient than relying on all the contents of Wikipedia, ii) the smaller, in return less diversified Spanish Wikipedia works almost always much better as a training corpus for bilingual mappings than the ubiquitously used English Wikipedia.
Blog Development as A Resource for Geographic Learning in SMAN Kecamatan Percut Sei Tuan

An effective learning process is a learning process that uses various forms of learning resources. This study aims to determine blogs' feasibility as a source of learning geography for material management of Indonesia's natural resources at SMAN Percut Sei Tuan District. This research was conducted in the odd semester of the 2019/2020 school year, with a population of all class XI IPS students at SMAN 1 Percut Sei Tuan consisting of 4 classes with a total of 139 students and class XI IPS at SMAN 2 Percut Sei Tuan which consisted of 2 courses with the number of 69 students. The study sample was class XI IPS 1 at SMAN 1 Percut Sei Tuan, totaling 35 students, and class XI IPS 1 at SMAN 2 Percut Sei Tuan amounted to 33 students. This research is development research using the Borg and Gall model with ten steps of research implementation. The data collection technique used was a questionnaire. The data analysis technique used is descriptive. The results showed that the validation of the feasibility of blogs as a source of learning geography carried out in 2 stages showed that in the first stage of verification, the acquisition of the feasibility of a blog as a source of learning geography was (87.27%) with criteria worthy of revision as needed. After making improvements according to the assessors' input, the results of the stage 2 validation obtained the feasibility of a blog as a source of learning geography (93.89%) with very feasible criteria without revision.
The Use of YouTube based Interactive Learning Media in Giving English Subject Material for Middle School Students

The research objective is to see eight grade students’ perception of the use of interactive learning media based on YouTube in giving English subject material. The reason of researcher did this research is because the educators at the junior high school use YouTube as a learning medium which is expected so that students can understand the material being studied, so that students can continue to follow the teaching and learning process during the pandemic, especially in English subjects. This study used a qualitative research with narrative inquiry approach and thematic analysis to see the response of the use of YouTube. In order to get accurate results, the researchers used questionnaire and interviews. The subjects of this study were 8th grade students in one of junior high school in Karawang who are familiar with using YouTube as a media. Based on the results of the study, that had been conducted on the use of YouTube-Based interactive media to giving English material was that 4 out of 5 eighth grade students at one of junior high school in Karawang liked and were happy with the way teachers delivered material through YouTube videos during this pandemic because they become the focus of learning and the material becomes easy to understand.
Identification of Information Source Use Patterns in the Students’ Distance Learning Process at the Surabaya University, Indonesia

As the digital native generation, students need good information literacy skills. Although information literacy education has been introduced at the Surabaya State University, it has not provided in-depth knowledge. This study identifies patterns of information sources used by students and provides an overview of student information literacy skills, such as understanding their information needs and retrieval, especially during the pandemic. The study was conducted with a qualitative approach using interviews to collect data collection. The informants included 14 Surabaya State University students selected through purposive sampling and analysed using Thematic Analysis. The findings indicate that the pattern needs to be improved, from the choosing, the search process, and information sources. Furthermore, universities need to improve digital information literacy programs provided by libraries and facilitate access for students to use them as needed.
PENGARUH BUERGER ALLEN EXERCISE TERHADAP NILAI ANKLE BRACHIAL INDEX PADA PASIEN DIABETES MELITUS

Diabetes mellitus is a disorder of the endocrine system characterized by increased levels of glucose in the blood. The purpose of this study was to assess the effect of Buerger's Allen exercise on the value of the ankle brachial index (ABI) in patients with diabetes mellitus. The research design was a quasi-experimental pretest and posttest without a control. The study was conducted from March to May 2021 at Grandmed Lubuk Pakam Hospital with 48 respondents, with consecutive sampling technique. Data were analyzed using the Wilcoxon test. The Buergers Allen exercise intervention was performed twice a day, for three weeks. The procedure is performed by lifting the lower extremities up at an angle of 45-90 degrees for 2-3 minutes, then the patient sits at the bedside with the legs hanging down, accompanied by flexion, extension, pronation and supination movements for 5-10 minutes, and the patient lies down. with both feet resting for 10 minutes. There was a significant effect between the mean ABI value before intervention 0.83 and after intervention 0.95, p=0.00. The difference in mean ABI p=0.000, p&lt;0.05. The results of the study concluded that there was an effect of buerger allen exercise on the ABI value before and after the intervention where the ABI value was getting better. It is recommended for nurses to make Buergers Allen exercise one of the independent nursing interventions in providing nursing care to patients with diabetes mellitus.
RANCANG BANGUN KURSI RODA ELEKTRIK BERBASIS INTERNET OF THINGS (IOT)

Wheelchairs are mobility devices that are often used by people who have difficulty walking on their feet, due to illness, injury, or disability. Most of the wheelchairs that exist today are still using the manual system. Ideally, a wheelchair is needed so that users feel free and comfortable in adjusting the wheelchair movement according to their wishes.&#x0D; This study aims to make an innovation in the form of designing an electric wheelchair based on the internet of things (IoT). In this tool, there are several integrated electronic components such as NodeMCU, voltage sensor that is connected to the android smartphone application. Delphi XE8 software functions to create control applications that can be controlled via a smartphone. The control system on a smartphone uses an internet connection to process the wheelchair control system. This tool is very dependent on the connection and stability of the internet network.&#x0D; Design of electric wheelchair based IoT, has the performance that a wheelchair can carry a maximum load of 30kg at a speed of 0.79m / second, plus an accumulator / battery load and a 6.4kg DC motor, so that the total load can be under of 36.4kg.
Coreference by Appearance: Visually Grounded Event Coreference Resolution

Event coreference resolution is critical to understand events in growing number of online news with multiple modalities including text, video, speech, etc.However, the events and entities depicting in different modalities may not be perfectly aligned and can be difficult to annotate, which makes the task especially challenging with little supervision available.To address the above issues, we propose a supervised model based on attention mechanism and an unsupervised model based on statistical machine translation, capable of learning the relative importance of modalities for event coreference resolution.Experiments on a video multimedia event dataset show that our multimodal models outperform text-only systems in the event coreference resolution task.A careful analysis reveals that the performance gain of the multimodal model especially under the unsupervised setting comes from better learning of visually salient events.
An Effective Progressive Image Transmission using Superpixel based Saliency Detection and Modified SPIHT Compression Algorithm

A new progressive image transmission system was proposed in this research paper for effective usage of communication bandwidth. At first, the superpixel based saliency detection method was used for segmenting the foreground region from the background region, because it gives more saliency information of an image with the benefit of color contrast. Then, Integer Wavelet Transform (IWT) was applied in the foreground image, which delivers A good quality of the image and also the compression ratio of the image was decent. Additionally, optimized neural network and modified Set Partitioned in Hierarchical Tree (SPIHT) algorithm were applied in the background image that delivers good rate distortion properties in the noise free environment and also enhances the image visual experience. In modified SPIHT, the sub-tree roots were not excluded that helps to encode and quantize the wavelet coefficients effectively. Also, it delivers more information to the image edges that effectively improves the subjective visual experience. Experiment report showed that the proposed work enhanced the Peak Signal to Noise Ratio (PSNR) upto 5dB compared to the existing work.
Workflow towards autonomous and semi-automized UXO Survey and Detection

This paper presents a workflow for UXO detection based on multibeam data in combination with AUV-based ground truth. An artificial neuronal network (ANN) is trained on manually annotated multibeam data and aims for making UXO detection and the generation of target lists faster and more objective. Prior to annotation the data is checked according to several quality factors to ensure that it fits for the purpose of object detection. The quality and accuracy of annotations has an influence on the predicted probabilities of the ANN, as the probabilities of the annotations determined by the experts are considered during training.
Veronica Ujcich, Grammatica dei bambini: le parole, Roma, Carocci, 2020. Diana Vedovato e Vera Zanette, Grammatica dei bambini: la frase, Roma, Carocci, 2021.

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How to Stimulate People to Take Care of Products? – The Development of a Toolkit for Designers

Taking care of products is an important aspect of sustainable consumer behaviour, because it is an appropriate approach to prolong products' lifetimes. Although consumers in general agree on this and demonstrate a general motivation to take care of their products, previous research has shown that they struggle to repair, maintain or treat their products carefully in daily life. Design has the potential to increase consumers' product care activities, but more knowledge and distinct strategies are needed by designers to purposefully design for this behaviour. We used three different approaches – a workshop with design students, an analysis of already existing products and services that have implemented aspects of product care, and an ideation session – to create eight strategies and 24 substrategies that can stimulate product care through design. These eight strategies are informing, enabling, social connections, appropriation, control, awareness, antecedents & consequences, and reflecting. To support designers in the implementation of these strategies, we transferred these strategies into a toolkit, which can be used in the product development process of different kinds of products. This paper describes the development of the product care strategies as well as the Product Care Toolkit.
Educational Barriers of the Economic Security of the EAEU

The object of scientific research within the framework of this article is ways of overcoming barriers and exemptions on the way of the implementation by the member states of the Eurasian Economic Union of their international obligations on the mutual recognition of education. To achieve this goal, an analysis was carried out of the reasons for the ineffectiveness of the obligations declared at the level of the integration association to recognize in one of the EAEU member states documents on education and (or) qualifications, documents on academic degrees and titles obtained in another state of the Union. The author substantiated the possibility of using the tools of professional and public accreditation of educational programs in the context under consideration, subject to expanding the territorial boundaries of its implementation and recognizing the significance of the results obtained within the integrated educational space. The proposed measures for the implementation and implementation of these instruments at the international level will ensure the effectiveness of the freedom of movement of labor within the studied integration association.
Improving Privacy Guarantee and Efficiency of Latent Dirichlet Allocation Model Training Under Differential Privacy

Latent Dirichlet allocation (LDA), a widely used topic model, is often employed as a fundamental tool for text analysis in various applications.However, the training process of the LDA model typically requires massive text corpus data.On one hand, such massive data may expose private information in the training data, thereby incurring significant privacy concerns.On the other hand, the efficiency of the LDA model training may be impacted, since LDA training often needs to handle these massive text corpus data.To address the privacy issues in LDA model training, some recent works have combined LDA training algorithms that are based on collapsed Gibbs sampling (CGS) with differential privacy.Nevertheless, these works usually have a high accumulative privacy budget due to vast iterations in CGS.Moreover, these works always have low efficiency due to handling massive text corpus data.To improve the privacy guarantee and efficiency, we combine a subsampling method with CGS and propose a novel LDA training algorithm with differential privacy, SUB-LDA.We find that subsampling in CGS naturally improves efficiency while amplifying privacy.We propose a novel metric, the efficiency-privacy function, to evaluate improvements of the privacy guarantee and efficiency.Based on a conventional subsampling method, we propose an adaptive subsampling method to improve the model's utility produced by SUB-LDA when the subsampling ratio is small.We provide a comprehensive analysis of SUB-LDA, and the experiment results validate its efficiency and privacy guarantee improvements.