Reviewerly/exHarmony huggingface dataset:
BERT Cannot Align Characters

In previous work, it has been shown that BERT can adequately align cross-lingual sentences on the word level. Here we investigate whether BERT can also operate as a char-level aligner. The languages examined are English, Fake English, German and Greek. We show that the closer two languages are, the better BERT can align them on the character level. BERT indeed works well in English to Fake English alignment, but this does not generalize to natural languages to the same extent. Nevertheless, the proximity of two languages does seem to be a factor. English is more related to German than to Greek and this is reflected in how well BERT aligns them; English to German is better than English to Greek. We examine multiple setups and show that the similarity matrices for natural languages show weaker relations the further apart two languages are.
Bank of Ireland Tests Meetings in Virtual Reality

This paper summaries a case study conducted by Meetingroom and Bank of Ireland in exploring the use of virtual reality to conduct meetings online. The case study was to compare virtual reality meetings to traditional video teleconferencing software. The results point to the improved feelings of presence, closeness, and arousal for virtual reality environments, but also demonstrate a difference in the experience for female and male participants. In particular, the use of avatars instead of real-life video images of the participants was preferred by female participants which point to a possible de-biasing ability for virtual reality environments.
Improve discoverability and recognition for your research activities with ORCID

Improve discoverability and recognition for your research activities with ORCID was presented via webinar on April 14, 2021.
Intensional Kleene and Rice theorems for abstract program semantics

Classical results in computability theory, notably Rice's theorem, focus on the extensional content of programs, namely, on the partial recursive functions that programs compute. Later work investigated intensional generalisations of such results that take into account the way in which functions are computed, thus affected by the specific programs computing them. In this paper, we single out a novel class of program semantics based on abstract domains of program properties that are able to capture nonextensional aspects of program computations, such as their asymptotic complexity or logical invariants, and allow us to generalise some foundational computability results such as Rice's Theorem and Kleene's Second Recursion Theorem to these semantics. In particular, it turns out that for this class of abstract program semantics, any nontrivial abstract property is undecidable and every decidable over-approximation necessarily includes an infinite set of false positives which covers all the values of the semantic abstract domain.
Discovering the Style Information in Texts via A Reinforced Decision Process

This paper focuses on the word disentanglement-based approaches for text style transfer. The related systems first remove the style attribute words in the given texts and then generate the target sentences using the remained neutral templates. Previous work retrieves the style words using intuitive heuristics, which lacks in-depth analysis and can hardly provide a precise word detection. The resulting error will further affect the generation phase and leads to the failure of the style transformation. In this paper, we formalize the style detection task as a dynamic decision process; each word in the given text is classified as a style or neutral content sequentially leveraging the word property, the context, and the decision history. As no background labels indicating the attribute words, reinforcement learning is deployed in our model. An evaluation (reward) function is designed to quantify the style shift and content loss simultaneously, providing an accurate estimation for the decision process. The efficiency of the proposal is verified on two types of style transfer tasks, i.e., sentiment transfer and formality transfer. The experimental results demonstrate the model's competitive performance compared to the state-of-the-art baselines once equipped with an insertion-based generation approach.
Augmented Reality as a Research Tool, for the Knowledge and Enhancement of Cultural Heritage

Starting from a reflection on the new role of digital technology in this pandemic situation, and particularly the role of AR for Cultural Heritage, this paper presents two AR applications.The first is used to share the analyses carried out on the Pantheon surveys realized between the seventeenth and nineteenth centuries.The second is about the illusionistic dome in the Church of Sant'Ignazio in Rome, realized by Andrea Pozzo.These two applications can display three-dimensional models superimposed onto images and original drawings, and also two-dimensional contents: the results of graphical analysis carried out on digital copies.The final aim of this ongoing research is to develop some AR multimedia content, linked to semantic concepts.
Roda De Conversa Virtual Com Idosos Em Tempos De Pandemia: Experiência Da Residência Multiprofissional

Objective: To describe the experience of a Family and Community Multiprofessional Residency Program team in health education actions for the elderly, using the virtual conversation wheel as an approach. Methods: This is a descriptive study, experience report type, referring to a virtual conversation circle carried out by residents in family and community health, in the categories of Physiotherapy, Nutrition and Psychology, with emphasis on the elderly population. The conversation circles were held from February to March 2021 with an average of 50 elderly people from the Open University for the Elderly (UNATI) of Teresina – Piaui. Results and Discussion: The virtual conversation wheel was successful and contributed to a comprehensive discussion of all the themes raised on the multidisciplinary perspective. The need for continuity of care, and to bring health education to the population safely using the digital mode, allowed greater reach of information, enabling the dissemination of content for the elderly, providing moments of socialization, awareness and sharing to this extract of the society. Conclusion: In view of the social isolation caused by the COVID-19 pandemic, resident professionals and the elderly public had the challenge of re-adapting, reinventing and learning new forms of communication and health care, through actions through virtual means, characterized as an effective tool to encourage social isolation and health promotion.
IMPLEMENTASI MODEL PEMBELAJARAN QUANTUM TEACHING DALAM MENINGKATKAN KECAKAPAN HIDUP (LIFE SKILL) PADA MATA PELAJARAN FIQIH TERHADAP SISWA MTs TUT WURI HANDAYANI MEDAN

The purpose of this study was to determine the application of the Quantum Teaching model in improving students' life skills in the field of Fiqh. In addition, to find out the advantages and disadvantages in the application of the Quantum Teaching model. The method used in this research was classroom action research (CAR). This research method was carried out in the field of Fiqh by using the Quantum Teaching model to improve students' life skills in the field of Fiqh. Before conducting the research, the researcher conducted a pre-cycle (pre-study), and continued with the implementation of research with several cycles. In this case, what is meant by a cycle is a cycle of sequential activities that return to the original step, where each cycle consists of four stages, namely; planning, action, observation, and reflection). The results showed that students' life skills in the field of Fiqh through the application of the Quantum Teaching model had increased. This increase could be seen from the results of the beginning of cycle 1 (pretest) for the Life Skills instrument in which 16 people (44.5%) got the positive category and 20 people (55.6%) got the negative category.. Then at the end of cycle 1 (posttest) it increased to as many as 20 people (55.5%) got the positive category and 16 people (44.4%) got the negative category. While in cycle 2, the results of the beginning of cycle 2 (pretest) for life skills instruments showed that 26 people (72.2%) got a positive category and 10 people (27.8%) got a negative category.  Then at the end of cycle 2 (posttest) it increased to as many as 30 people (83.3%) got the positive category and 6 people (16.7%) got the negative category. Thus the indicators of the purposes of this research have been achieved, meaning that using Quantum Teaching model was effective in improving students' life skills.
Federated User Clustering for non-IID Federated Learning

Federated Learning (FL) is one of the leading learning paradigms for enabling a more significant presence of intelligent applications in networking considering highly distributed environments while preserving user privacy. However, FL has the significant shortcoming of requiring user data to be Independent Identically Distributed (IID) to make reliable predictions for a given group of users. We present a Neural Network-based Federated Clustering mechanism capable of clustering the local models trained by users of the network with no access to their raw data. We also present an alternative to the FedAvg aggregation algorithm used in traditional FL, which significantly increases the aggregated models' reliability in Mean Square Error by creating several training models over IID users.
Bidirectional Regression for Arbitrary-Shaped Text Detection

Arbitrary-shaped text detection has recently attracted increasing interests and witnessed rapid development with the popularity of deep learning algorithms. Nevertheless, existing approaches often obtain inaccurate detection results, mainly due to the relatively weak ability to utilize context information and the inappropriate choice of offset references. This paper presents a novel text instance expression which integrates both foreground and background information into the pipeline, and naturally uses the pixels near text boundaries as the offset starts. Besides, a corresponding post-processing algorithm is also designed to sequentially combine the four prediction results and reconstruct the text instance accurately. We evaluate our method on several challenging scene text benchmarks, including both curved and multi-oriented text datasets. Experimental results demonstrate that the proposed approach obtains superior or competitive performance compared to other state-of-the-art methods, e.g., 83.4\(\%\) F-score for Total-Text, 82.4\(\%\) F-score for MSRA-TD500, etc.
Level of Effectiveness of Using Zoom Meeting Application as a Learning Media on Students of IAI Muhammadiyah Sinjai

This study aims to (1) Knowing the level of effectiveness of the use of the zoom meeting application for students of the Faculty of IAI Muhammadiyah Sinjai and (2)Knowing what factors affect the effectiveness of using the zoom meeting application in the online learning process for IAI Muhammadiyah Sinjai students.The results of the study show that (1) The level of effectiveness of using the Zoom Meeting application as a learning medium for students of the Faculty of Economics and Islamic Law IAI Muhammadiyah Sinjai is on an effective scale with a percentage of 60.7%, which means that students agree to use the zoom application in the teaching and learning process and further information delivery, students are quite satisfied in using the Zoom meeting application because the application can be accessed for free besides it is easy to use by students.students (2) factors that affect the effectiveness of using the zoom meeting application as a learning medium for students of the Islamic law and economics faculty of IAI muhammadiyah sinjai, namely the use of the zoom meeting application can support distance learning because the presentation of learning remains visual, verbal, and saves time, and information contained in it can be accessed again.
Research Guides: Library 101: Technology

This guide will take you through the ins and outs of your library! Learn about services, policies, and all of the opportunities that await you!
Dynamic selection of classifiers for Content Based Image Retrieval

In this paper, we present a new framework for Content Based Image Retrieval (CBIR), based on Dynamic Ensemble Selection (DES) of classifiers. Herein, the classifiers consist of Convolutional Neural Networks (CNNs) that output the class probability vector of each input image. First, a diverse ensemble is built by training several weak classifiers on different training subsets, from the retrieval database. Then, each training image is passed throughout all the candidate classifiers to extract its class probability vector. These extracted vectors are then combined to make its final representation. When a new query image is input, the level of competence of all the candidate classifiers is measured on the region of competence of this image, in the training set. Then, only the most competent classifiers are selected to extract the class probability vectors from each query image. They are then combined to make a more discriminant image representation. To the best of our knowledge DES has never been applied to the CBIR area, which is the novelty of our research. The obtained results demonstrate the effectiveness of the dynamic selection, compared to the use of all the ensemble members, in terms of precision, recall, and mean average precision.
Forms of interaction between enterprises and educational structures in the training of personnel for regional innovative enterprises

The article discusses educational practices and forms of interaction among enterprises, universities, colleges, educational centers and other structures in the process of training for innovative enterprises of Ulyanovsk region. In this regard, some differences in the approaches of new industries and enterprises that have existed since the Soviet era are indicated. In particular, this concerns the development of various intracorporate retraining and advanced training programs, including their own educational centers. At the same time, such formats are not devoid of the contradictions and are different for workers and specialists, for universities’ and colleges’ graduates. In general, the development of innovation sector poses new requirements for training and readiness of the education system to take into account the constantly changing demands of enterprises with new technologies and new products. On the other hand, the role of non-institutional forms of training of employees, their desire to improve, develop and the ability to independently search for and receive new knowledge in constantly changing conditions are emphasized. In this regard, the ability to self-study, including the involvement of online educational portals was highlighted. The importance of the early orientation of children to study technical disciplines and the role of children’s technology parks, joint school classes with innovative enterprises, and the importance of interregional competence centers for secondary special education was emphasized.
Bridging the Last Mile: Utilizing QR codes, e-Paper and Smartphones to Link Low-Power IoT Data Collection Devices to the Internet

Anstract- While wireless technologies are common solutions to the last mile problem for IoT systems, challenges exist with devices that are in remote locations, sparse deployments, have power and cost constraints, and low data applications as the cost of wireless and the supporting infrastructure presents barriers to entry. This work presents a last mile solution relying on smartphones to bridge the gap between the data generation device and the internet. A unique, low-power solution is presented based on QR codes and e-paper displays that allows a user's smartphone to carry the power and processing burden for data transmission. Utilizing the persistent nature of e-paper displays with low power requirements, QR codes can efficiently communicate data with minimal power impacts to a device's power budget and create large communication windows for user data pickup, leveraging the power of the smartphone without the need for extensive user training and costly infrastructure.
Pelatihan Penggunaan Libreoffice Bagi Para Guru SD Tanah Tingal

LibreOffice is a FOSS (Free Open Source Software) office application which is a project of The Document Foundation (TDF) organization. LibreOffice is used to create text documents, spreadsheets, presentations, and so on. LibreOffice is a solution for using an alternative use of Microsoft Office office applications with a paid license. LibreOffice uses the Mozilla Public License (MPL) version 2.0. Domestic Primary Schools in the use of ICT for teaching and learning activities have started pioneering migration using the Linux operating system and the FOSS application in 2015. Starting in the 2016/2017 academic year, it is planned to fully implement it. use of Linux for teachers, administrative staff and students. To support this, the school is doing various things to improve the competence of teachers in the use of ICT, especially the LibreOffice office application. Based on this, Training on the Use of LibreOffice for Tanah Tingal Elementary teachers to improve teacher competence in the use of ICT in teaching and learning activities at Tanah Tingal School as a form of Community Service Program (PPM) which is one one tridharma from college. This training can be a useful contribution to improving the abilities of teachers in particular and students in the end.
Consumer Fraud Detection via P-feature Conversion

The rapid development of tourism economy has brought new challenges such as the prevention of consumer fraud for smart city applications. Traditional fraud detection approaches such as telecommunication fraud and credit card fraud detection need a data set containing both the normal behavior and abnormal behavior. Therefore, they are incompetent to address such challenges in the tourism market where the data set is open and very few records of fraud behaviors are available. To address this issue, we propose a P-feature conversion algorithm to construct third-party features to expose the outliers. These features reveal the internal characteristics of different businesses and their useful internal connections. Then, we build a fraud detection model for tourism based on the Local Outlier Factor anomaly detection algorithm. Experimental results show that our model can effectively identify fraudulent merchants in the tourism market.
Perancangan dan Pengembangan Video Company Profile PT. Dua Utama Jaya

PT. Dua Utama Jaya is a company that engaged in training and certification and located in Batam City. This company has been established since 2004 and focuses on providing internationally certified training to support industry, construction, oil, And gas. The problem experienced by the company is the lack of information about services and only through brochures, websites, and through individuals. Therefore, the company requires media information about the Company Profile to inform the public in introducing the company. The methodology applied in this research is the Applied research. To produce a good and quality company profile video-based media design, it is used for supporting applications such as Adobe Premiere CS6 and Filmora. The results of the Video Company Profile will be uploaded to the Youtube Platform owned by PT. Two Utama Jaya. Provide Information about The Company to The Public and Improve The Image for The Company
Research on Web Robot Detection Technology for Concept Drift

Abstract Web robots have long been significant participants of the internet and the detection is deemed to be essential. Contemporary web robot detection techniques lack the ability to detect when the characteristics of web robots drastically change over time, namely a phenomenon called concept drift. Such change of web robot’s behavior may lead to the deterioration of detection model performance. In order to maintain high detection performance over time, in this paper, we propose a novel web robot detection framework that consists of a model pool, a reinforcement learning algorithm integrating all the models and a concept drift detection module. First, we employ reinforcement learning to integrate a number of detection models that targets different types of web robots, by dynamically adjusting model weights. Then we apply the drift detection method (DDM) to monitor concept drift and identify the need to retrain the model over time. Experiments are conducted using real website datasets under concept drift. The results demonstrate that our model significantly outperforms the state-of-the-art approaches.
Kontrol Robot Menggunakan Gerakan Mata Berbasis Sinyal Electrooculography (EOG)

Biomedical technology has now been widely adopted as a means of monitoring the human body in real-time. For example, to detect eye movement. In the medical world, eye movement can be used to determine the type of disease. With the application of human-machine interface (HMI) technology, eyeball movement can be developed in the robotics industry as robot navigation. For example, by moving the eyeball left and right, the robot can interpret the eye signal to move left and right. The interaction between the eyeball movement and the robot is of particular concern in this study. This study aimed to design a measuring instrument for eye movement detection using Electrooculography (EOG) techniques to move a wheeled robot. The EOG measuring instrument consisting of an instrument differential amplifier, a low pass filter, and a high pass filter has been applied in this research. The signal generator technique on EOG is carried out by placing electrodes on three sides of the face, namely forehead (G), left horizontal (H-), right horizontal (H +). The experimental results showed a significant difference between the left and right eye movement amplitude signals. This amplitude is used to classify the movement of the robot wheel towards the left and right. The process of sending robot signals and EOG measuring instruments uses Bluetooth HC-05 serial communication. Based on the research results, it is proven that the robot manages to move left and right according to the eyeball movement.
Challenges in the digital preservation of historical laminated manuscripts

In this paper, we analyze and discuss the characteristics of a system for the effective digital preservation and fruition of historical manuscripts degraded by the process of lamination. The most significant degradation caused by lamination is that the parchment or paper support loses its flatness, and usually presents ripples and warpings. This, together with the affixed translucent varnish, dramatically impair the digital acquisition process, so that light reflections in the more disparate directions affect the digital images. A digital system to contrast this irreversible and progressive degradation and to enable an effective access to the fragile asset should provide a number of functionalities: specialized digitization, able to avoid reflections as much as possible; image enhancement, devised to correct the residual degradations and enhance the text for an easier legibility; semi-automatic transcription of the virtually restored pages; and, finally, scholarly encoding and linguistic analysis, which should adapt existing tools to the specificity of the primary source (writing system and language). As a case study, we will make reference to the ``Poem in Rajaz on medicine'', written by Abubacer in the XII century, and conserved in the Al Quaraouiyine Library located in Fez, Morocco. The feasibility study for the realization of such a system is of general utility, in that it can provide guidelines for the digitization, the enhancement and the text encoding of the many laminated manuscripts conserved in other historical archives. On the other hand, from the cultural heritage point of view, the experimentation on the ``Poem in Rajaz on medicine'' could foster the systematic philological and ontological study of a unique piece of our documental heritage: the longest poem of medieval Islamic medical literature.