Reviewerly/exHarmony huggingface dataset:
Open Science, the alliance way

Universities are challenged with creating an enabling environment for Open Science, including policies, technical infrastructure, services, training and support and cross-cutting issues such as FAIR research data management and Open Access. In many universities, staff and skills to supply are in high demand and the level of implementation is often lower than the strategic importance given to Open Science (EUA, 2021). Collaboration is crucial to address these challenges, be efficient and avoid duplication of efforts across higher education institutions and other stakeholders. European university alliances are one mechanism that supports such collaborations (Council of the EU, 2021). In the EUTOPIA European University, an alliance consisting of 10 member universities from across Europe, an ambitious work programme has been developed and is implemented through several projects funded by Erasmus+ and Horizon 2020. EUTOPIA understands Open Science as a core pillar, recognizing that knowledge needs to be accessible for everyone. Therefore, our alliance aims to mainstream Open Science across the network and create closer policy alignment between individual alliance members. We do so by addressing different dimensions relevant for Open Science, from policies over to joint training and support, as well as coordinating these activities across the alliance and policy alignment (implemented in a subsidiary way). Overall, our activities cover: Building technical infrastructure, although challenging across institutional and national boundaries, through a collaboration with OpenAIRE. This will facilitate FAIRness of our research results and FAIR-compliance of institutional repositories. Training and guidance on crucial issues such as research data management, Open Access, Citizen Science, and reproducible research for different target audiences. A framework policy for research assessment &amp; metrics considering Open Science as a cross-cutting issue. Citizen science receives special attention through the establishment of a community of practice and regular citizen science clinics, informal meet-ups to share experience, approaches and challenges in Citizen Science. A template Open Science policy to be implemented in modular fashion by partner universities and the creation of an alliance-wide Open Science office. In short, European Universities are an important vehicle for connecting Open Science expertise and capacity across higher education institutions. They allow for the integration and efficient use of local expertise and networks for the benefit of the academic community of all members. Moreover, they are platforms for experimentation and sharing experience among partners with a focus on producing tangible results and improvements. We believe that alliances such as EUTOPIA are important tools to advance Open Science in Europe.
Estimating Related Words Computationally Using Language Model from the Mahabharata an Indian Epic

‘Mahabharata’ is the most popular among many Indian pieces of literature referred to in many domains for completely different purposes. This text itself is having various dimension and aspects which is useful for the human being in their personal life and professional life. This Indian ‘epic is originally written in the Sanskrit Language. Now in the era of natural language processing, artificial intelligence, machine learning, and human-computer interaction, this text can be processed according to the domain requirement. It is interesting to process this text and get useful insights from Mahabharata. The limitation of the humans while analyzing Mahabharata is that they always have a sentiment aspect toward the story narrated by the author. Apart from that, the human cannot memorize statistical or computational details, like which two words are frequently coming in one sentence? What is the average length of the sentences across the whole literature? Which word is the most popular word across the text, what are the lemmas of the words used across the sentences? Thus, in this paper, we propose an NLP pipeline to get some statistical and computational insights along with the most relevant word searching method from the largest epic ‘Mahabharata’. We stacked the different text processing approaches to articulate the best results which can be further used in the various domains where Mahabharata needs to be referred.
Supporting equity, economies of scale, and interoperability by applying the International Data Space model to open science usage and impact reporting

The OA Book Usage Data Trust effort (www.oabookusage.org) is exploring how an International Data Space (IDS) could address issues of trust, data quality, and resource-burdens for OA usage data reporting and analytics. Currently individual libraries, publishers, and scholarly publishing platforms and services must normalize, curate, and aggregate their usage and impact metrics as provided from numerous platforms. While well-resourced organizations may have the time and expertise to curate and aggregate open and privileged usage data across provided COUNTER-compliant and non-COUNTER compliant reports; smaller presses, publishers, and innovative projects often lack the resources necessary to process incoming usage data and benefit from robust OA impact analytics. To address this disparity and improve the quality and interoperability of OA book usage data, OA book publishing stakeholders are exploring how to adopt the international data space (IDS) models and standards. Awarded 1.2Million USD by the Mellon Foundation, a team led by OPERAS, OpenAIRE, the University of North Texas, and Johns Hopkins University are hosting community consultations to determine what data stewardship and security practices are needed to achieve trusted direct usage data exchange at scale.
IMRecoNet: Learn to Detect in Index Modulation Aided MIMO Systems with Complex Valued Neural Networks

Index modulation (IM) reduces the power consumption and hardware cost of the multiple-input multiple-output (MIMO) system by activating part of the antennas for data transmission. However, IM significantly increases the complexity of the receiver and needs accurate channel estimation to guarantee its performance. To tackle these challenges, in this paper, we design a deep learning (DL) based detector for the IM aided MIMO (IM-MIMO) systems. We first formulate the detection process as a sparse reconstruction problem by utilizing the inherent attributes of IM. Then, based on greedy strategy, we design a DL based detector, called IMRecoNet, to realize this sparse reconstruction process. Different from the general neural networks, we introduce complex value operations to adapt the complex signals in communication systems. To the best of our knowledge, this is the first attempt that introduce complex valued neural network to the design of detector for the IM-MIMO systems. Finally, to verify the adaptability and robustness of the proposed detector, simulations are carried out with consideration of inaccurate channel state information (CSI) and correlated MIMO channels. The simulation results demonstrate that the proposed detector outperforms existing algorithms in terms of antenna recognition accuracy and bit error rate under various scenarios.
Generalized Closed-form Formulae for Feature-based Subpixel Alignment in Patch-based Matching

Cost-based image patch matching is at the core of various techniques in computer vision, photogrammetry and remote sensing. When the subpixel disparity between the reference patch in the source and target images is required, either the cost function or the target image have to be interpolated. While cost-based interpolation is the easiest to implement, multiple works have shown that image based interpolation can increase the accuracy of the subpixel matching, but usually at the cost of expensive search procedures. This, however, is problematic, especially for very computation intensive applications such as stereo matching or optical flow computation. In this paper, we show that closed form formulae for subpixel disparity computation for the case of one dimensional matching, e.g., in the case of rectified stereo images where the search space is of one dimension, exists when using the standard NCC, SSD and SAD cost functions. We then demonstrate how to generalize the proposed formulae to the case of high dimensional search spaces, which is required for unrectified stereo matching and optical flow extraction. We also compare our results with traditional cost volume interpolation formulae as well as with state-of-the-art cost-based refinement methods, and show that the proposed formulae bring a small improvement over the state-of-the-art cost-based methods in the case of one dimensional search spaces, and a significant improvement when the search space is two dimensional.
Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems

Adversarial attacks, e.g., adversarial perturbations of the input and adversarial samples, pose significant challenges to machine learning and deep learning techniques, including interactive recommendation systems. The latent embedding space of those techniques makes adversarial attacks difficult to detect at an early stage. Recent advance in causality shows that counterfactual can also be considered one of ways to generate the adversarial samples drawn from different distribution as the training samples. We propose to explore adversarial examples and attack agnostic detection on reinforcement learning-based interactive recommendation systems. We first craft different types of adversarial examples by adding perturbations to the input and intervening on the casual factors. Then, we augment recommendation systems by detecting potential attacks with a deep learning-based classifier based on the crafted data. Finally, we study the attack strength and frequency of adversarial examples and evaluate our model on standard datasets with multiple crafting methods. Our extensive experiments show that most adversarial attacks are effective, and both attack strength and attack frequency impact the attack performance. The strategically-timed attack achieves comparative attack performance with only 1/3 to 1/2 attack frequency. Besides, our black-box detector trained with one crafting method has the generalization ability over several other crafting methods.
Digital Literacy in Building a Smart City at Banda Aceh

The commitment to innovative city-based development must begin with the presence of digital communities that become users and take advantage of all the smarts presented in a smart city. Strengthening digitalization in society by utilizing all the technology offered by the government is interesting to study. Banda Aceh is one of the first cities in Aceh Province to implement the bright city concept successfully; the choice in this study is where the digital literacy strategy in urban communities is the focus. This study aims to describe and analyze digital literacy strategies and their obstacles in building a smart city in Banda Aceh City. This study also uses a descriptive qualitative approach with data collection techniques using observation, interviews, and documentation studies. The data analysis technique used in this study is an interactive model through three main things: data reduction, data presentation, and conclusion. The results of the study found that digital literacy in building a smart city in the Banda Aceh City government by; First, Providing Smart City Technical Guidance, developing intelligent city policies and institutions, conducting readiness analysis and setting targets, introducing smart cities through social media, Cooperating with the community and actively descending to the village, as well as cooperating with other work units, and Infrastructure Development. The obstacles include the government, budget, community, and public organizations. Furthermore, some people are less responsive and use digital literacy for people with disabilities.
DESIGN OF COMMUNAL WASTEWATER TREATMENT PLANT (CASE STUDY IN DEPOK VILLAGE, TRENGGALEK, EAST JAVA)

Planning for a communal scale Wastewater Treatment Plant (WWTP) in Depok Village, Trenggalek Regency, East Java is needed because most of the wastewater in Depok Village is only treated with septic tanks. This study aims to plan a communal scale WWTP design based on the generation of domestic and non-domestic wastewater in Depok Village. The WWTP planning in this study was carried out based on the results of laboratory test parameters for pH, TSS, BOD, COD, total coliform, fatty oil, and ammonia. Based on the test results, it is known that the parameters exceed the required limits according to the Minister of Environment Regulation No. 68 of 2016 is the parameter of TSS, ammonia, and total coliform. The units that are planned are barscreen unit is planned to have a length of 8.65 m, a width of 2.65 m, and a depth of 3 m. The initial settling basin is planned to have a length of 11 m, a width of 3 m, and a depth of 4 m. The anaerobic biofilter unit is planned to have a length of 15 m, a width of 7.5 m, and a depth of 2.5 m. The aerobic biofilter unit is planned to have a length of 16.5 m, a width of 8.5 m, and a depth of 2 m. The final settling basin is planned to have a length of 37 m, a width of 18.5 m and a depth of 2.5 m. The control body is planned to have a length of 9.5 m, a width of 5 m and a depth of 2 m. Meanwhile, disinfection is planned using a disinfectant pump.
Interlinked and integrated research support services

This poster introduces the efficient set of research support services available in University of Jyväskylä’s (JYU) Open Science Centre (OSC). The set includes several essential services for researchers to help them execute an open and responsible research process. The continuous improvement of research support services has led to an interlinked, integrated and harmonious set of technical solutions, processes and workflows which meet the needs of researchers and help them implement open science and FAIR policies in practice. They also save time and enable better working processes for the researchers but also for the experts conducting these services. The poster describes two main services which are interlinked and which both aim to make processes and workflows effortless. One of the main services is when metadata from research information system Converis is utilized using API in the self-archiving process of research articles to the institutional repository. OSC’s experts record the publication metadata on behalf of researchers and the same metadata of the publications is used in the self-archiving process. Also, data harvesting is used to get notification of new publications of researchers affiliated to JYU. Often the researchers don’t even have to inform OSC when their new publication is out. This effortless process combines two different systems (CRIS and institutional repository) and connects workflows regarding them. The poster also introduces a dynamic research data management tool which enables a fluent data management process. The goal of the development of this tool has been to free the researchers of having to learn the use of several different systems. The tool helps the researchers to track the handling process of their data and guides through all the necessary phases of the data management process. Again, the data once recorded is being utilized in other systems and in other phases of the whole process. Both the tool and the data management process it enables are integrated to other systems which are needed for example in storing and sharing the research data.
Pengaruh Media Pembelajaran Berbasis Macromedia Flash Terhadap Kemampuan Komunikasi Matematis Siswa

This study aims to analyze the effect of learning media based on Macromedia Flash on students' mathematical communication skills. This type of research is a quasi-experimental research with a quantitative approach. The population in this study were class IX students at MTs Darussalam Bengkulu City in the 2021/2022 academic year. The research sample was selected using a purposive sampling technique by taking into account the students' initial abilities. 18 students of class IX.A were chosen as the experimental class using macromedia flash-based learning media and 19 students of class IX.B were the control class with conventional learning. Data was collected through observation, tests, and questionnaires. Data analysis was carried out with the anacova test statistic. The results of this study indicate that there is an effect of learning media based on macromedia flash on students' mathematical communication skills with test results t_count=3,523&gt;t_table=2,028. Learning using macromedia flash-based media can bridge students in communicating mathematical concepts so that they can be used by teachers in other materials.
INFORMATION TECHNOLOGIES AS A LEARNING CHALLENGE FOR STUDENTS WITH MODERATE INTELLECTUAL DISABILITY

This paper shows some of the challenges that emerge while teaching Information Technologies to students with a moderate degree of intellectual disability. The authors present and summarize the possible perspectives of both teachers and students during the teaching process of this school subject.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0753/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
WRITING JOB APPLICATION LETTER AND RESUME WITH GOOGLE DOCUMENT: AN EXPERIMENTAL RESEARCH

One of the main skills that must be mastered by vocational students, especially in the Department of Office Automation &amp; Governance (OTKP) is understanding the script layout in English correspondence activities. Considering the urgency of the letter that will be used frequently in the future, and based on discussions with the class teacher at the research locus, the researcher focused on studying the writing of job application letters and resumes in English written by the vocational students. In addition, with the development of writing technology by Google Document (Google Docs/GDocs), it is hoped that it can facilitate students' writing assignments. This research is an experimental study that examines the effectiveness of Google Docs in writing job application letters and resumes in English. The research was conducted through pre-test, post-test and Forum Group Discussion (FGD) in order to provide input on research results. The results shows that through the t test, it is found that Google Docs is effective in writing English correspondence compared to writing letters manually in class X OTKP of SMK Negeri 1 Salatiga.
RESOURCES USED BY TEACHERS TO TEACH MATH, PHYSICS, CHEMISTRY AND BIOLOGY AT SECONDARY SCHOOL ONLINE

This research was meant to find which resources were used by teachers to teach Math, Physics, Chemistry and Biology online during the pandemic, trying to identify the main problems related to the adapting of the available resources, how they were -or not- adapted and the new ones. Besides, student’s feedback was considered, for example, if there were online classes, how tasks were sent and how they were checked and evaluated. The notion of the resource proposed by Adler (2012) was adopted by generating a survey to collect data. The survey has 21 items in total, 20 of them with closed answers, 2 of them with a Likert scale and an open question presented in an online format for all the teachers in every province in Argentina. The survey is a tool to analyse the appropriation and use of the resources by teachers of secondary school when teaching online.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0457/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
Implementasi Gerakan Literasi Sekolah Pada Era New Normal di SMA Negeri 3 Banjarmasin

GLS is one of the efforts to make schools into learning organizations whose citizens are literate, but in this new normal era, school literacy activities carried out at SMA Negeri 3 Banjarmasin are quite hampered, so that it can make students reading interests decrease. The purpose of this study was to analyze the implementation of GLS in the new normal era at SMA Negeri 3 Banjarmasin. The research method used in this study uses a descriptive quantitative approach. Questionnaires were distributed to 36 teachers at SMA Negeri 3 Banjarmasin. The results of the research conducted indicate that the total score obtained from filling out 36 questionnaires is 1.869, so an average value of 51,9 is obtained, which corresponds to the level that refers to the Policy Research Center, Ministry of Education and Culture. It can be concluded that the score is 51,9 is at a moderate level (38-52), so the school literacy movement at SMA Negeri 3 Banjarmasin is included in the sufficient category.Keywords: Implementation, new normal, school literacy movement
Analisis Kemampuan Klasifikasi Berbasis Obyek untuk Pemetaan Perubahan Penggunaan Lahan Sebagian Kabupaten Jember menggunakan Citra Landsat 8

Land is a complex system that requires good management. Along with population growth, it will result in an impact of increasing both the quality and quantity of life necessities that can change land use. This research is deemed necessary to make an interpretation using remote sensing. The use of remote sensing (PJ) is very important in presenting spatial information related to the appearance of an area. The purpose of this study is to assess the accuracy and analyze object-based classification for mapping land use change in parts of Jember Regency using Landsat 8 imagery. The method is used in this study uses Object Based Image Analysis (OBIA), optimal box classifier for the classification process, visual interpretation. segmentation results to classify land use changes. Based on the results of the land use / cover classification capability test in Kaliwates, Sumbersari, Pakusari, Mayang and Silo Districts using the OBIA method, it shows an accuracy value of 94.28% for Landsat 8 images recorded in 2015, and an accuracy value of 98.57% for images. Landsat 8 recording for 2020.
Attention based Occlusion Removal for Hybrid Telepresence Systems

Traditionally, video conferencing is a widely adopted solution for telecommunication, but a lack of immersiveness comes inherently due to the 2D nature of facial representation. The integration of Virtual Reality (VR) in a communication/telepresence system through Head Mounted Displays (HMDs) promises to provide users a much better immersive experience. However, HMDs cause hindrance by blocking the facial appearance and expressions of the user. To overcome these issues, we propose a novel attention-enabled encoder-decoder architecture for HMD de-occlusion. We also propose to train our person-specific model using short videos (1-2 minutes) of the user, captured in varying appearances, and demonstrated generalization to unseen poses and appearances of the user. We report superior qualitative and quantitative results over state-of-the-art methods. We also present applications of this approach to hybrid video teleconferencing using existing animation and 3D face reconstruction pipelines.
Directional Lifting Wavelet Transform for Image Edge Analysis

In this paper, we propose a new two-dimensional directional discrete wavelet transform that can decompose an image into 12 multiscale directional edge components. The proposed transform is designed in a fully discrete setting and thus is easy to implement in actual computations. The proposed transform is viewed as a category of redundant discrete wavelet transforms implemented by fast in-place computational algorithms by a lifting scheme that has been modified to incorporate redundancy. The redundancy is limited to $(N \times J+1)/4$, where $N=12$ is the directional selectivity and $J$ is a decomposition level of the multiscale transform. Numerical experiments in edge detection using various images demonstrate the advantages of the proposed method over some conventional standard methods. The proposed method outperforms several conventional edge detection methods in identifying both the location and orientation of edges, and well captures the directional and geometrical features of images.