Reviewerly/exHarmony huggingface dataset:
Strategic Partnerships of Universities as a Tool for Intensifying the Development of the Regional Economy and Society in Digital Economy

The article is devoted to topical issues of strategic partnership of universities with subjects of regional economy and society in digital economy.An overview of the tools for effective strategic partnership of universities at the regional level in digital economy, which can be used for its individual positioning, is given.The tools were developed taking into account the needs and capabilities of the existing regional ecosystem.The system of regional development and synergetics of its components is considered from the position of a university, as one of the key "players" in order to optimally build process models of individual bilateral partnerships.Integration of regional universities leads to increase in educational potential and consolidation of the entire regional community.This will increase the effectiveness of the regional higher education system through the formation of a unified educational space, integrated marketing, scientific unity, and an integrated business education system.Strategic partnership of enterprises belonging to territorial production clusters with universities and leading research centers allows making new discoveries, creating innovations, knowledge, training highly qualified specialists, and also contributes to stable economic growth and competitiveness of a region in digital economy.It also needs to take into account the speed of rapid technological development, the growing demand for more flexible digital ecosystems and effective strategic solutions to manage the digital future.
Forward-Secure Multi-User Aggregate Signatures Based on zk-SNARKs

As a solution to mitigate the key exposure problems in the digital signature, the forward security has been proposed. The forward security guarantees the integrity of the messages generated in the past despite leaks of a current time period secret key by evolving a secret key on each time period. In this paper, we propose a new forward secure aggregate signature scheme utilizing recursive zk-SNARKs (zero knowledge Succinct Non-interactive ARguments of Knowledge). Our proposal has constant complexities in key/signature sizes, signature generation, and verification time. The proposed forward secure signature scheme can aggregate signatures generated by multiple users as well as a single user. The security of the proposed scheme is formally proven under zero-knowledge assumption and random oracle model. The experiment results show that our signature scheme yields 12 s for signing time, 1 ms for verification time, 25 s for aggregation time, with the 1.6 KB secret key size and signature size independent of the number of time periods.
Symbiotic Design Application in Healthcare: Preventing Hospital Acquired Infections

Any clinical decision support (CDS) design project integrating computational technologies with clinician workflows will require the merging of multiple perspectives and fields of expertise in multidisciplinary teams. Much like the tools these teams aim to create, the team itself will need to continuously build, monitor, and repair a mutually beneficial relationship between each of its members. From our experience during the early development stages of an AI-enabled CDS tool for hospital-acquired infection (HAI) prevention, we abstract three central tenets of a symbiotic design process we have found to be vital for aligning goals, priorities, mental models, and techniques among a multidisciplinary team: (1) recurrent bottom-up feedback, (2) continual model (re-)alignment, and (3) openness to co-direction. With regards to these tenets, we discuss the successes and challenges our team has faced during the symbiotic design process through a series of vignettes and how these experiences coalescing diverse human design teams can influence the design of human-machine teams.
NICT-2 Translation System at WAT-2021: Applying a Pretrained Multilingual Encoder-Decoder Model to Low-resource Language Pairs

In this paper, we present the NICT system (NICT-2) submitted to the NICT-SAP shared task at the 8th Workshop on Asian Translation (WAT-2021).A feature of our system is that we used a pretrained multilingual BART (Bidirectional and Auto-Regressive Transformer; mBART) model.Because publicly available models do not support some languages in the NICT-SAP task, we added these languages to the mBART model and then trained it using monolingual corpora extracted from Wikipedia.We fine-tuned the expanded mBART model using the parallel corpora specified by the NICT-SAP task.The BLEU scores greatly improved in comparison with those of systems without the pretrained model, including the additional languages.
Reconstruction enhancement via projection screening in holographic tomography

This paper presents an algorithm for automatic detection of erroneous amplitude and phase components of a sample’s optical field, acquired by a holographic tomograph with a limited angle of projection. By applying image processing methods and statistical analysis to find and remove unfit projections, the quality of tomographic reconstruction of a 3D refractive index distribution of an object is greatly improved. The proposed methods can find their application in preprocessing of data in holographic tomography. Full Text: PDF ReferencesA. Kuś, W. Krauze, P. L. Makowski, and M. Kujawińska, "Holographic tomography: hardware and software solutions for 3D quantitative biomedical imaging (Invited paper)", ETRI Journal, 41, 1 (2019). CrossRef V. Balasubramani et al., "Phase unwrapping in ICF target interferometric measurement via deep learning", Appl. Opt., 60, 10 (2021). CrossRef Y. Park, C. Depeursinge, and G. Popescu, "Quantitative phase imaging in biomedicine", Nature Photonics, 12, 10 (2018). CrossRef W. Krauze, P. Makowski, M. Kujawińska, and A. Kuś, "Generalized total variation iterative constraint strategy in limited angle optical diffraction tomography", Opt. Express, 24, 5 (2016). CrossRef D. Ryu et al., "A non-calorimetric approach for investigating the moisture-induced ageing of a pyrotechnic delay material using spectroscopies", Sci Rep, 9, 1 (2019). CrossRef B. S. Lipkin, Picture Processing and Psychopictorics. (Saint Louis, Elsevier Science 2014). DirectLink A. M. Taddese, N. Verrier, M. Debailleul, J.-B. Courbot, and O. Haeberlé, "Optimizing sample illumination scanning in transmission tomographic diffractive microscopy", Appl. Opt., 60, 6 (2021). CrossRef
Recursive prosody is not finite-state

This paper investigates bounds on the generative capacity of prosodic processes, by focusing on the complexity of recursive prosody in coordination contexts in English (Wagner, 2010).Although all phonological processes and most prosodic processes are computationally regular string languages, we show that recursive prosody is not.The output string language is instead parallel multiple context-free (Seki et al., 1991).We evaluate the complexity of the pattern over strings, and then move on to a characterization over trees that requires the expressivity of multi bottom-up tree transducers.In doing so, we provide a foundation for future mathematically grounded investigations of the syntax-prosody interface.
Assessments of Solar, Thermal and Net Irradiance from Simple Solar Geometry and Routine Meteorological Measurements in the Pannonian Basin

In this paper, we discussed several different procedures for calculating irradiation from routine weather measurements and observations. There are between four and eight frequently used parameterizations of radiation balance components in meteorological preprocessors, and we investigated them. First of all, the estimated and measured solar and net irradiance were compared. Afterwards, the estimated and measured longwave irradiance were investigated. Then, we recalculated the net irradiance from the sum of global solar irradiance, longwave downwelling irradiance, reflect solar irradiance and upwelling longwave irradiance. Statistical estimates of the described methods were also recalculated compared with each shortwave and longwave radiation budget component measured separately with WMO first-class radiation instruments (Kipp&amp;Zonen CMP6 and CMP11 and CGR3 and CGR4) in the Agrometeorological Observatory Debrecen, Hungary during one-year time period. Finally, we compared the calculated and measured values for longer periods (2008–2010 and 2008–2017) through statistical errors. The suggested parameterizations of the net radiation based on the separately parameterized all radiation balance components were: Foken’s calculation for clear sky solar global irradiance, Beljaars and Bosveld parameterization for albedo, Dilley and O’Brien methodology for the clear sky incoming longwave (LW) irradiance and Holstlag and Van Ulden cloudiness correction for all sky incoming LW and for the LW outgoing irradiance.
Enhancing Business Communication Skills: An Action Research

This collaborative action research involving a lecturer and a student researcher intended to enhance a group of final-year students’ business communication skills to prepare them for employment. This study deployed the action research cycle: Identify-Plan-Act-Reflect. The pre-test results found that students had difficulties communicating confidently and interacting clearly in group discussions, and they were unable to exhibit good impression and perception during the discussions. Therefore, a teaching intervention was designed and executed to improve confidence in communicating, clarity when speaking and improvise business etiquette in a group discussion among the students. The five elements emphasized in the teaching intervention are business etiquette, pronunciation, discourse management, interactive communication and confidence. The post test results showed that the intervention has significantly improved the students’ confidence and pronunciation. This indicates that the action research study managed to enhance students’ business communication competencies.
Occlusion Handling by Successively Excluding Foregrounds for Light Field Depth Estimation Based on Foreground-Background Separation

This paper proposes a depth from light field (DFLF) method specifically to deal with occlusion based on the foreground-background separation (FBS). The FBS-based methods infer the disparity maps by accumulating the binary maps which divide whether each pixel is the foreground or background. Although there have been widely studied to handle the occlusion problem with the cost-based method, there are not enough researches to handle the occlusion problem with the FBS-based methods yet. We found that errors around the occlusion boundary in the resulting disparity maps of the FBS-based methods arise from the fattened foreground by the light field reprameterization. To avoid fattened foregrounds, the inferred foreground maps in the front region with respect to the disparity axis could be utilized in the back region in the three-dimensional volume construction, which corresponds to the cost volume construction in the cost-based methods. With the front-to-back scanning manner of the FBS-based method, by successively excluding inferred foreground maps, errors around occlusion boundary could be effectively reduced in the resulting disparity maps. With synthetic and real LF images, the proposed method shows reasonable performance compared to the existing methods and better performance than existing FBS-based methods.
Violence Detection over Online Social Networks: An Arabic Sentiment Analysis Approach

&lt;p class="0abstract"&gt;Today, the influence of the social media on different aspects of our lives is increasing, many scholars from various disciplines and majors looking at the social media networks as the ongoing revolution. In Social media networks, many bonds and connections can be established whether being direct or indirect ties. In fact, Social networks are used not only by people but also by companies. People usually create their own profiles and join communities to discuss different common issues that they have interest in. On the other hand, companies also can create their virtual presence on the social media networks to benefit from this media to understand the customers and gather richer information about them. With all of the benefits and advantages of social media networks, they should not always be seen as a safe place for communicating, sharing information and ideas, and establishing virtual communities. These information and ideas could carry with them hatred speeches that must be detected to avoid raising violence. Therefore, web content mining can be used to handle this issue. Web content mining is gaining more concern because of its importance for many businesses and institutions. Sentiment Analysis (SA) is an important sub-area of web content mining. The purpose of SA is to determine the overall sentiment attitude of writer towards a specific entity and classify these opinions automatically. There are two main approaches to build systems of sentiment analysis: the machine learning approach and the lexicon-based approach. This research presents the design and implementation for violence detection over social media using machine learning approach. Our system works on Jordanian Arabic dialect instead of Modern Standard Arabic (MSA). The data was collected from two popular social media websites (Facebook, Twitter) and has used native speakers to annotate the data. Moreover, different preprocessing techniques have been used to show their effect on our model accuracy. The Arabic lexicon was used for generating feature vectors and separate them to features set. Here, we have three well known machine learning algorithms: Support Vector Machine (SVM), Naive Bayes (NB) and k-Nearest Neighbors (KNN). Building on this view, Information Science Research Institute’s (ISRI) stemming and stop word file as a result of preprocessing were used to extract the features. Indeed, several features have been extracted; however, using the SVM classifier reveals that unigram and features extracted from lexicon are characterized by the highest accuracy to detect violence.&lt;/p&gt;
A Multi-Loop Vehicle-Counting Method under Gray Mode and RGB Mode

With the rapid development of road traffic, real-time vehicle counting is very important in the construction of intelligent transportation systems (ITSs). Compared with traditional technologies, the video-based method for vehicle counting shows great importance and huge advantages in its low cost, high efficiency, and flexibility. However, many methods find difficulty in balancing the accuracy and complexity of the algorithm. For example, compared with traditional and simple methods, deep learning methods may achieve higher precision, but they also greatly increase the complexity of the algorithm. In addition to that, most of the methods only work under one mode of color, which is a waste of available information. Considering the above, a multi-loop vehicle-counting method under gray mode and RGB mode was proposed in this paper. Under gray and RGB modes, the moving vehicle can be detected more completely; with the help of multiple loops, vehicle counting could better deal with different influencing factors, such as driving behavior, traffic environment, shooting angle, etc. The experimental results show that the proposed method is able to count vehicles with more than 98.5% accuracy while dealing with different road scenes.
The Underlying Order Induced by Orthogonality and the Quantum Speed Limit

We perform a comprehensive analysis of the set of parameters {ri} that provide the energy distribution of pure qutrits that evolve towards a distinguishable state at a finite time τ, when evolving under an arbitrary and time-independent Hamiltonian. The orthogonality condition is exactly solved, revealing a non-trivial interrelation between τ and the energy spectrum and allowing the classification of {ri} into families organized in a 2-simplex, δ2. Furthermore, the states determined by {ri} are likewise analyzed according to their quantum-speed limit. Namely, we construct a map that distinguishes those ris in δ2 correspondent to states whose orthogonality time is limited by the Mandelstam–Tamm bound from those restricted by the Margolus–Levitin one. Our results offer a complete characterization of the physical quantities that become relevant in both the preparation and study of the dynamics of three-level states evolving towards orthogonality.
A Survey on Human-Computer Interaction in Spatial Augmented Reality

<p indent=0mm>Spatial augmented reality (SAR), which typically uses projectors to augment physical spaces with virtual contents, is one of the three main forms of augmented reality. In SAR systems, users can interact with virtual contents in physical spaces, therefore they have good environmental, spatial and collaborative perceptions. SAR systems can also reduce the cognitive load of interaction tasks. SAR display forms are firstly demonstrated, and then SAR architectures are illustrated as well as its technical principles. SAR interaction technologies are classified into 6 categories, which are touch based interaction, gesture or posture based interaction, 3D controller based interaction, handholding projector interaction, tangible interaction, and multimodal interaction. Challenges from 3D registration, virtual-real fusion are analyzed. The application status in the field of sports, medical treatment, education, entertainment and art are discussed. The trends in SAR interaction are finally predicted. Specifically, SAR interaction will become more natural, more intelligent in occlusion processing, more widely applicable, more closely related with the social, cultural and psychological researches, and novel display approaches will also be used by SAR systems.
Getting to Production with Few-shot Natural Language Generation Models

Peyman Heidari, Arash Einolghozati, Shashank Jain, Soumya Batra, Lee Callender, Ankit Arun, Shawn Mei, Sonal Gupta, Pinar Donmez, Vikas Bhardwaj, Anuj Kumar, Michael White. Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue. 2021.
Using project method for the purpose of educating future music teachers

The article discusses the specifics of applying project method to the educational process. The analysis of scientific materials that concern themselves with applying project method is carried out, their main principles are highlighted, and a project model is proposed. Studies conducted in the field of project method were used as materials for this work. During the research, methods of analysis, synthesis, comparison, deduction and induction were used. The research hypothesis is based on the assumption that applying project method to the training process of future music teachers will help students with improving their professional competencies, and increase the motivation to learn. The study proved that applying project method to the training process of educating future music teachers allows for better pedagogical training, motivating students to work more actively, display creativity, and identity. The project method allows students to receive skills of independent and group work, short and long-term planning, and self-assessment. General positive characteristics of applying project method to the training process of educating future music teachers proves the need to adopt this method in higher education institutions. This paper is intended for teachers and students who will implement creative projects while receiving music education.
Information Retrieval System in the Bible

Information retrieval is used to search for relevant documents so that they can be obtained quickly and precisely. There are many Christians who want to study the gospel. However, often experience problems in finding the Gospel verse and topics dealing with the need to search by the user. Therefore, have to search individually, each verse in the four Gospels to find the topic or verse that the user wants to find out. In this study, the authors used the Bible verses in the Gospels as documents, so that these verses could be searched for the level of relevance or similarity to the entered keywords. Furthermore, to determine the level of relevance between documents and keywords is calculated using the Vector Space Model. Based on the application that has been successfully built, the application can be show 10 documents related to the keywords that are searched and sorted from the most relevant, with the highest similarity value, namely 78.65%.Keywords - Information Retrieval, Vector Space Model, Bible.
Efficiency Rainwater Harvesting at the Roof Campus Buildings

Rainwater harvesting is implemented appropriately by striving to use costs that are quite cheap and efficient, but still has many benefits for meeting clean water needs. In this study, the rainwater harvesting model to be analyzed was using the cistern method. The advantage is that it is easier to apply, the amount of water collected is quite large, and it does not require a large area of land. By implementing a culture of harvesting rainwater, can get several benefits, including reducing runoff which can prevent the UTU campus area from inundation and flooding. The average volume of rainwater that can be harvested using a 5-year return period is 110581.12 liter/day with an average volume of water requirements of 7452.09 liters/day. From the results of the rainwater harvesting analysis, it can be concluded that this method is capable of being applied where the analysis results show that the harvested rainwater can meet the water needs of users on the Teuku Umar University campus. In the future, it will be planning where the excess water stored in the cistern will be channeled into infiltration wells to maintain groundwater sources sustainably.
Analisis Minat Belajar Siswa Menggunakan Media Pembelajaran E-comic Aritmatika Sosial Masa Pandemi Covid-19

The Covid-19 pandemic has become a trending topic of conversation for the past year until now, this pandemic has changed various aspects of human life today, especially in the world of education. This causes students' failure to understand mathematical concepts and students' lack of interest in learning. This study aims to describe students' learning interest in the use of E-comic media in social arithmetic material during the Covid-19 pandemic. This research is a descriptive quantitative research. The sample of the research was the seventh grade students of SMP which consisted of 15 students who were taken randomly. The instrument used in this study is a non-test instrument in the form of a student learning interest questionnaire distributed using Google Form in social arithmetic learning using E-comic which consists of 20 statements as a reference to determine students' interest in learning in the use of E-comic media. The data analysis technique used in this research is quantitative descriptive analysis. The results of this study indicate that the use of E-comic learning media is effective on student learning interest during the Covid-19 pandemic with the percentage results80.67% classified as very high criteria. So that the E-comic learning media is very effectively used as a medium for learning mathematics to increase student interest in learning during the Covid-19 pandemic.Keywords: analysis, E-comic, social arithmetic, covid-1 pandemicÂ