Reviewerly/exHarmony huggingface dataset:
Real-Time Cow Detection and Identification Using Enhanced Particle Filter

Abstract In this paper, demonstration of how an individual cow can be tracked and identified in a herd of cows using an enhanced particle filter is presented. In a typical agricultural setup, it is not uncommon to witness cases of cow swapping and rustling. In the past, different methods were recorded in literatures for the monitoring of herds. However, advancement in technology has rendered those methods less effective, resulting to demand for continual improvement on the state-of-the-art methods for tracking individual cows. To achieve this, we employed off-the-shelf networks for end-to-end individual cow identification in up-to-down motionless imagery acquired from stationary camera. The dynamic trajectory of the herd was captured by a camera installed on a pole near a passageway through which the cows passed almost every day and the video processing system was employed for the processing of the herd’s trajectory. Report was made on the model initialisation, mean shift algorithm, particle-Kalman filter, and the target model is updated in order to overcome the change in the target object appearance over time. To our utmost knowledge, this work is the first to apply combination of mean-shift based tracker and particle-Kalman filter as enhanced particle filter to real-time cow detection and identification to curtail occlusion and non-linear tracking problem.
Enumerating all bilocal Clifford distillation protocols through symmetry reduction

Entanglement distillation is an essential building block in quantum communication protocols. Here, we study the class of near-term implementable distillation protocols that use bilocal Clifford operations followed by a single round of communication. We introduce tools to enumerate and optimise over all protocols for up to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>5</mml:mn></mml:math> (not necessarily equal) Bell-diagonal states using a commodity desktop computer. Furthermore, by exploiting the symmetries of the input states, we find all protocols for up to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>8</mml:mn></mml:math> copies of a Werner state. For the latter case, we present circuits that achieve the highest fidelity with perfect operations and no decoherence. These circuits have modest depth and number of two-qubit gates. Our results are based on a correspondence between distillation protocols and double cosets of the symplectic group, and improve on previously known protocols.
Analysis of Research Trends Based on Text Mining in the Journal of Korean Society of Environmental Engineering

Objectives : The purpose of this study is to analyze research trends based on text mining technology from the published papers in the Journal of Korean Society of Environmental Engineering.Methods : From 2000 to 2019, a total of 2,743 published papers were analyzed using text mining techniques. Term frequency, TF-IDF for document classification, word association analysis were applied to find the characteristics of text data.Results and Discussion : When confirming the high appearance of the word in the published paper during 2000-2019, ‘adsorption’, ‘heavy metals’, ‘activated carbon’, ‘sediment’, ‘sewage sludge’ was found in order. It implies that large number of studies in the journal were focused on the water quality field mainly. TF-IDF analysis classified the studies into five groups; 1) drinking water treatment field, 2) water quality modeling field, 3) heavy metal adsorption field, 4) biological sewage treatment field, 5) environmental catalyst field. These results by TF-IDF show that a large proportion of studies were published in the field of water quality modeling and biological sewage treatment. When we analyzed the term frequency every five years, “adsorption” and “heavy metals” were the highly-frequency occurrence words from 2000 to 2009, but in the last 5 years, new words such as “fine dust”, “cesium”, and “ecological toxicity” were appeared. It seems that the research was reflected in the recent environmental issues.Conclusions : A lot of studies has been focused on the field of water quality but in recent years, new research topics are being studied related to atmosphere, toxicity, and radiation. Applying a more sophisticated and diverse text mining technique will be of great help to improve the environmental engineering research field.
User Testing with Microinteractions

Enabling and supporting discoverability of research outputs and datasets are key functions of university and academic health center institutional repositories. Yet adoption rates among potential repository users are hampered by a number of factors, prominent among which are difficulties with basic usability. In their efforts to implement a local instance of InvenioRDM, a turnkey next generation repository, team members at Northwestern University’s Galter Health Sciences Library &amp; Learning Center supplemented agile development principles and methods and a user experience design-centered approach with observations of users’ microinteractions (interactions with each part of the software’s interface that requires human intervention). Microinteractions were observed through user testing sessions conducted in Fall 2019. The result has been a more user-informed development effort incorporating the experiences and viewpoints of a multidisciplinary team of researchers spanning multiple departments of a highly ranked research university.
Fine-Grained Complexity of Regular Path Queries.

A regular path query (RPQ) is a regular expression q that returns all node pairs (u, v) from a graph database that are connected by an arbitrary path labelled with a word from L(q). The obvious algorithmic approach to RPQ evaluation (called PG-approach), i. e., constructing the product graph between an NFA for q and the graph database, is appealing due to its simplicity and also leads to efficient algorithms. However, it is unclear whether the PG-approach is optimal. We address this question by thoroughly investigating which upper complexity bounds can be achieved by the PG-approach, and we complement these with conditional lower bounds (in the sense of the fine-grained complexity framework). A special focus is put on enumeration and delay bounds, as well as the data complexity perspective. A main insight is that we can achieve optimal (or near optimal) algorithms with the PG-approach, but the delay for enumeration is rather high (linear in the database). We explore three successful approaches towards enumeration with sub-linear delay: super-linear preprocessing, approximations of the solution sets, and restricted classes of RPQs.
Learning in virtual space: an intergenerational pilot project.

Introduction: More and more educational institutions are discovering the advantages of settings for digital teaching and learning and the technology of virtual reality (VR). This also holds true for the BZ Pflege in the field of continuing education with age-heterogeneous groups of participants. The question arises whether baby-boomers and X and Y generation learners accept, understand and perceive the digital form of learning with VR glasses as beneficial for their learning. Project description: A course has been developed with the goal of teaching the anatomy of the heart by immersive visualisation. A questionnaire was used to determine how the use of VR glasses influenced participants` learning, acceptance, understanding and cognitive load. Results: The participants reacted positively to the VR technology. The new learning technology did not lead to cognitive overload. Participants indicated that they were able to link new knowledge with already existing knowledge. They also found the VR glasses easy to use. Conclusion: From the perspective of participants and project management alike, it can be said that age- heterogeneous groups present no obstacle for new innovative teaching methods, such as the use of VR glasses.
#TecnoEduUNLP en tiempos de aislamiento: oportunidades y tensiones

The lockdown (locally known as ASPO: Social, Preventive and Compulsory Lockdown) that has been in place since March 2020 in Argentina led the institutions of higher education to start teaching in virtual modality in order to assure the implementation of the academic calendar. This situation has challenged us to revise the contents, teaching methodologies, communication with and between students and the digital tools used, among others changes.In this new scenario, the Chair of Educational Technology in the School of Humanities and Education of the Universidad Nacional de La Plata adjusted its approach to these new conditions mainly by using a virtual classroom and a videoconference system.In this article we analyze the tensions we have been experiencing during this year because of these new teaching conditions. These tensions have become opportunities since we were able to capitalize on our prior experience of working together: the reaffirmation of the teaching model centered on the student, the visibility of all pedagogical interventions, an increase in educational experiences using digital technologies, the irreducible tension between agents and tools (as expressed by Vigotsky), among others.First, we start this document with the description of the Educational Technology Chair, then we present the principal aspects of our teaching model in order for the readers to be able to identify the tensions and challenges in this situation.Last, we offer some preliminary ideas on the objectives achieved in the course during the first part of this year.
Fine-Grained Access Control Scheme Based on Improved Proxy Re-Encryption in Cloud

Cloud storage technology has attracted a considerable number of users owing to its exponential growth. Storing data in the cloud can save the resources of local storage configuration and reduce the cost of local hardware investment. However, the data stored in the cloud is out of the physical control (out of control) of the user. Based on the service characteristics of the cloud environment and the security requirements of user privacy data in the cloud environment, this paper proposes an improved identity proxy re-encryption algorithm based on the advanced encryption standard algorithm. The performance of the algorithm is optimized by reducing the number of bilinear mapping operations, whose calculation takes the longest time in the proxy re-encryption scheme. Only two bilinear mapping operations are required in this scheme. In addition, the encrypted data are tested to different degrees. The experimental results show that this scheme satisfies encryption and decryption performance requirements of the user.
Correction to: Computational Science and Its Applications – ICCSA 2020

In the version of this paper 27 was originally published the name of Marcela Velásquez Fernádez has been corrected to Marrcela Velásquez Fernández. In the version of this paper 44 was originally published the name of Łukasz Tomczyk – at appears with a “v” at the end of this family name. This has now been corrected.
A Comparative Study of Optimization Algorithms for Global Path Planning of Mobile Robots

It is an essential issue for mobile robots to reach the target points with optimum cost which can be minimum duration or minimum fuel, depending on the problem. In this paper, it was aimed to develop a software for the optimal path planning of mobile robots in user-defined two-dimensional environments with static obstacles and to analyze the performance of some optimization algorithms for this problem using this software. The developed software is designed to create obstacles of different shapes and sizes in the work area and to find the shortest path for the robot using the selected optimization algorithm. Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Genetic Algorithm (GA) were implemented in the software. These algorithms have been tested for optimum path planning in four models with different problem sizes and different difficulty levels. When the results are evaluated, it is observed that the ABC algorithm gives better results than other algorithms in terms of the shortest distance. With this study, the use of optimization algorithms in real-time path planning of land mobile robots or unmanned aerial vehicles can be simulated.
Cross-Domain End-To-End Aspect-Based Sentiment Analysis with Domain-Dependent Embeddings

With the development of sentiment analysis, studies have been gradually classified based on different researched candidates. Among them, aspect-based sentiment analysis plays an important role in subtle opinion mining for online reviews. It used to be treated as a group of pipeline tasks but has been proved to be analysed well in an end-to-end model recently. Due to less labelled resources, the need for cross-domain aspect-based sentiment analysis has started to get attention. However, challenges exist when seeking domain-invariant features and keeping domain-dependent features to achieve domain adaptation within a fine-grained task. This paper utilizes the domain-dependent embeddings and designs the model CD-E2EABSA to achieve cross-domain aspect-based sentiment analysis in an end-to-end fashion. The proposed model utilizes the domain-dependent embeddings with a multitask learning strategy to capture both domain-invariant and domain-dependent knowledge. Various experiments are conducted and show the effectiveness of all components on two public datasets. Also, it is also proved that as a cross-domain model, CD-E2EABSA can perform better than most of the in-domain ABSA methods.
Evaluation of the Functionality of GeoTube® based Physicochemical Faecal Sludge Treatment: A Cursory Alternate

With the rampant boom in faecal sludge (FS) collection and management in line with Indian government’s agenda, quite a few urban local bodies (ULBs) in Telangana such as Greater Warangal Municipal Corporation (GWMC) initiated into establishing faecal sludge treatment plant (FSTP) in collaboration with experienced private technology partners such as Banka BioLoo Limited. FSTPs were so designed with minimal mechanical components to regularize it as a popular choice for rural and sub-urban. The GeoTube based technology makes use of an organic flocculant to maximize the floc formation and thereby the water recovery. Post-flocculation the sludge is fed into a semi permeable polypropylene trap (GeoTube®) with a pore size of 0.3 mm. The method of dewatering the septage with the aid of GeoTube was so designed to ensure greater than 98% efficacy. Ultimately, the above effluent gets polished with a series of tertiary units such as pressure sand filter, activated carbon filter, UV disinfection, etc. The permeate meets the inland water disposal standards and is used to maintain the green belt in and around the plant. The trapped biosolids are self-composted for more than two months inside the filled tubes. Further, the debagged material is analyzed to ensure compliance with physico-chemical, metallic, and pathogenic limits. Afterward, the final materials pulverized, packed, and distributed amid the local farmers to be used as a soil conditioner. The FSTP has been successfully running for about two years now and has to date treated more than 2 million liters of septage of which recycled almost 1500 kL of water and 35 tons of biosolids.
Latent Graph Recurrent Network for Document Ranking

BERT based ranking models are emerging for its superior natural language understanding ability. The attention matrix learned through BERT captures all the word relations in the input text. However, neural ranking models focus only on the text matching between query and document. To solve this problem, we propose a graph recurrent neural network based model to refine word representations from BERT for document ranking, referred to as Latent Graph Recurrent Network (LGRe for short). For each query and document pair, word representations are learned through transformer layer. Based on these word representations, we propose masking strategies to construct a bipartite-core word graph to model the matching between the query and document. Word representations will be further refined by graph recurrent neural network to enhance word relations in this graph. The final relevance score is computed from refined word representations through fully connected layers. Moreover, we propose a triangle distance loss function for embedding layers as an auxiliary task to obtain discriminative representations. It is optimized jointly with pairwise ranking loss for ad hoc document ranking task. Experimental results on public benchmark TREC Robust04 and WebTrack2009-12 test collections show that LGRe (The implementation is available at https://github.com/DQ0408/LGRe ) outperforms state-of-the-art baselines more than $$2\%$$ .
Readability Assessment of Textbooks in Low Resource Languages

Readability is a fundamental problem in textbooks assessment. For low re-sources languages (LRL), however, little investigation has been done on the readability of textbook. In this paper, we proposed a readability assessment method for Tibetan textbook (a low resource language). We extract features based on the information that are gotten by Tibetan segmentation and named entity recognition. Then, we calculate the correlation of different features using Pearson Correlation Coefficient and select some feature sets to design the readability formula. Fit detection, F test and T test are applied on these selected features to generate a new readability assessment formula. Experiment shows that this new formula is capable of assessing the readability of Tibetan textbooks.
Academic Journal of Economic Studies

Academic Journal of Economic Studies Â is an Romanian academic publication, edited by â€œDimitrie Cantemirâ€ Christian University in Bucharest. TheÂ  Academic Journal of Economic Studies Â wants to become an important journal that publishes high quality original studies disseminates economic results of scientific research in economics from academic and business world.Â The journal focuses on promoting research worldwide, encouraging international dialogue and supports the exchange of ideas between researchers across the academic and business world. TheÂ  Academic Journal of Economic Studies Â is an open access journal and is a valuable scientific resource; published articles are available online without restriction to researchers, practitioners, students and other categories of users.Â The journalâ€™s frequency is quarterly.Â Monthâ€™s appearance will be: March, June, September and December. The journal encourages the submission of interdisciplinary studies, international empirical research and comparative analysis. Articles are accepted for publication after a rigorous, anonymous and impartial evaluation of each article separately by specialized scientific reviewers.
Image Data Security Mechanism Based on the Internet of Things Cardiac Catheterization Laboratory Information Management System Research and Design

With the development of science and technology, more and more operations are performed in the cardiac catheterization laboratory. During such operations, a lot of relevant imaging data need to be retained. These imaging data can be used for clinical and scientific research and teaching applications, but imaging data security has also become an increasingly important issue. This article is based on the Internet of Things cardiac catheterization laboratory information management system image data security mechanism system research. First of all, this article adopts the literature method to study the application research of the Internet of Things technology in the medical field, as well as the relevant medical imaging data security technology methods. Then, the medical image data security mechanism was designed, and the image data security model of the cardiac catheterization laboratory information management system based on the Internet of Things was established. Finally, the application of decentralized management of the Internet of Things RFID technology on medical equipment and the security of the application of this technology on medical imaging data are analyzed, and finally a conclusion is drawn. The image data security mechanism established in this article is based on the Internet of Things technology. The security rate of image information data reaches more than 95%, the information data security level reaches level 1, and the average data missing rate is only 4.7%. It is a brand-new breakthrough, hoping to further improve the efficiency of hospital information management and protect the safety of medical information.
Reflections on the Information Literacy of English Teachers in the Context of China’s Education Informatization 2.0

The promulgation of "Education Informatization 2.0 Action Plan" marks that China's education informatization has entered a new historical development stage.The context, mode, content of English language teaching in Chinese middle schools are faced with radical changes, too.English teachers themselves should reshape their educational ideas and professional roles, and integrate information technology into English language teaching.They sever as constructors of teaching knowledge system, constructors of teaching information environment, integrators of teaching information resources, and guides of students' personalized learning.The external forces such as schools, education authorities and the government should cultivate English teachers' information literacy from different perspectives.
Period-Wise Phase Unwrapping Method With Two Gray Level Coding Patterns

Fringe projection profilometry is a widely used three-dimensional (3D) optical measurement technique. However, it is quite challenging to quickly obtain the 3D information of objects. Minimizing the number of patterns for phase unwrapping is an efficient way to address the above problem, and many methods have been proposed. This paper reports a period-wise phase unwrapping method with only two gray level coding patterns. Due to a hybrid coding strategy implemented, the number of patterns used in the proposed method reduces by one in comparison with conventional gray level method when generating the same number of codewords. A robust decoding scheme is also developed to determine the fringe order, and its accuracy is guaranteed by using the self-correcting method to remove the phase errors. Some experiments have been conducted, and their results confirm that the success of the proposed method.
A Level Set Representation Method for $N$-Dimensional Convex Shape and Applications

In this work, we present a new efficient method for convex shape representation, which is regardless of the dimension of the concerned objects, using level-set approaches. Convexity prior is very useful for object completion in computer vision. It is a very challenging task to design an efficient method for high dimensional convex objects representation. In this paper, we prove that the convexity of the considered object is equivalent to the convexity of the associated signed distance function. Then, the second order condition of convex functions is used to characterize the shape convexity equivalently. We apply this new method to two applications: object segmentation with convexity prior and convex hull problem (especially with outliers). For both applications, the involved problems can be written as a general optimization problem with three constraints. Efficient algorithm based on alternating direction method of multipliers is presented for the optimization problem. Numerical experiments are conducted to verify the effectiveness and efficiency of the proposed representation method and algorithm.