Reviewerly/exHarmony huggingface dataset:
Patent Portfolio Analysis Related to Advanced VR Technologies and Applications for Treating Driving Phobia

Virtual reality technology enables people to interact with objects in three-dimensional simulated environments. The technology has been applied in many fields such as entertainment, education, and healthcare. Health treatment applications include psycho therapeutical treatments for post-traumatic stress disorders related to driving phobias. Patents that have been filed for treating patients diagnosed with driving phobias are searched and collected using global patent platforms including Derwent Innovation’s solution. Patent analytic methods, including clustering, key term frequency analysis, correlation matrix creation, Latent Dirichlet Allocation (LDA), and technology function matrix mapping, are applied to analyze the patent portfolio and identify key technology development trends. The research goal is to identify patent strategies related to driving-related virtual reality psychotherapy treatment. The research identifies six technology clusters, including virtual reality technologies, vehicle driving simulations, diagnosis of driving phobia through bio-signal analysis, and artificial intelligence for health systems. Based on the cluster analysis, virtual reality related patents are increasing over the last decade. A lesser number of patents focus on virtual reality technology that includes exposure therapy for driving phobia treatment. The patent mining results show that virtual reality exposure therapy for driving phobias is still in the growth stage. There is a research gap for new treatments for driving phobias and other phobias such as post-traumatic stress disorder, which have great potential for transdisciplinary engineering research.
Current Experience of Graduates’ Career Planning and Its Use for Identifying Requirements and Setting Goals for Career Centers at Universities

Every university graduate faces a problem of employment. A young specialist without work experience can hardly find a job by his/her specialization, which would allow them not only to use the acquired knowledge but also to get an adequate estimation of their efforts. Today Russian universities adopt the overseas experience in career promotion by helping graduates in their career planning, as today's higher education institutions in Russia are extremely interested in graduate's career development and at the same time in successful functioning of the university in general. The article grounds the necessity to set up Employment and Career Centers at universities, whose organizational and economic characteristics and trends of development can give an opportunity to accumulate and allocate the best practices of graduates' career planning and technical and technological support of interaction with business partners for different categories of graduates. Here a young specialist can find consultations of career experts, help in compiling a competitive CV and assistance in searching for a suitable vacancy. At the same time the Employment and Career Center at the university can carry out an important function of informing university employees about the necessity and importance of graduates' career planning and stimulating graduates' interest in self-organization and professional self-development.
Desain Game Edukasi Ilmu Tajwid Bagi Anak Usia Dini menggunakan Pemodelan Finite State Automata

This study discusses how Finite State Automata (FSA) can be used as a model to design a Tajweed Science game application as a business diagram. This study aims to facilitate early childhood in learning the science of recitation by grouping hijaiyah letters into grouping the science of recitation by using a touch of the hand. The type of automata theory used is a non-deterministic finite automata with epsilon transition (E) or better known as E-NFA. Each transition, input, state that exists from the NFA, is basically to show the characteristics or states that occur in a game application. The importance of this research, in addition to learning recitation from an early age, is to show that automata theory can be used to help design a system in making game applications. The results of this Tajweed Science game application design are a rough display because there will still be further development stages and can ensure that game applications can be built from E-NFA modeling.
KNEWTON ANALYTICAL REVIEW AS A PLATFORM FOR PERSONALIZATION OF LEARNING CONTENT

The article analyzes the theoretical basis of the adaptive learning platform Knewton, identifies the benefits and prospects for its use in the educational process. The Knewton platform, developed by the company of the same name (USA), became one of the first adaptive learning platforms in the world and is now the undisputed world leader in this context. It provides continuous adaptability, constantly accumulating data about each pupil / student and properly building an individual learning trajectory, forming appropriate recommendations in real time. Knewton itself does not develop ready-made courses, but provides the platform, which offers developers certain algorithms for adapting educational content. The theoretical basis of the Knewton platform is a number of models and approaches, including: theory of test problems (item response theory), probabilistic graph models (probabilistic graphical models), hierarchical agglomerative clustering. Among the Knewton tools that provide personalization of learning, we consider such as knowledge graph (knowledge graph), continuous reinforcement, learning curves (learning curves), student learning profile (student learning profile), network effects. The main advantages of Knewton for pupils / students include: instant "feedback", collaboration, gamification. The advantages for teachers are meeting the various needs of pupils / students, monitoring the progress of the whole class, monitoring the progress of an individual student, improving the content of educational programs. General recommendations for the development of an adaptive course based on Knewton (on the example of the Alta program) are given. Models of potential application of the Knewton platform are characterized: "face-to-face", "rotation", "flex", "online laboratory", "self-blend", "online user". Given that the practical experience of using adaptive learning systems, both in Ukraine and in the world as a whole, is quite insignificant, we believe that it is important to consider the theoretical foundations of these technologies, a critical assessment of their advantages and disadvantages, as well as prospects for implementation and use. In the future, we plan to develop recommendations for domestic teachers to create training courses based on the Knewton platform.
Automatic Text Summarization by Providing Coverage, Non-Redundancy, and Novelty Using Sentence Graph

The day-to-day growth of online information necessitates intensive research in automatic text summarization (ATS). The ATS software produces summary text by extracting important information from the original text. With the help of summaries, users can easily read and understand the documents of interest. Most of the approaches for ATS used only local properties of text. Moreover, the numerous properties make the sentence selection difficult and complicated. So this article uses a graph based summarization to utilize structural and global properties of text. It introduces maximal clique based sentence selection (MCBSS) algorithm to select important and non-redundant sentences that cover all concepts of the input text for summary. The MCBSS algorithm finds novel information using maximal cliques (MCs). The experimental results of recall oriented understudy for gisting evaluation (ROUGE) on Timeline dataset show that the proposed work outperforms the existing graph algorithms Bushy Path (BP), Aggregate Similarity (AS), and TextRank (TR).
A secure and efficient certificateless content extraction signature with privacy protection

Efficiency and privacy are the key aspects in content extraction signatures. In this study, we proposed a Secure and Efficient and Certificateless Content Extraction Signature with Privacy Protection (SECCESPP) in which scalar multiplication of elliptic curves is used to replace inefficient bilinear pairing of certificateless public key cryptosystem, and the signcryption idea is borrowed to implement privacy protection for signed messages. The correctness of the SECCESPP scheme is demonstrated by the consistency of the message and the accuracy of the equation. The security and privacy of the SECCESPP scheme are demonstrated based on the elliptic curve discrete logarithm problem in the random oracle model and are formally analyzed with the formal analysis tool ProVerif, respectively. Theory and experimental analysis show that the SECCESPP scheme is more efficient than other schemes.
Rank Algorithm of Web Education Resources Based on Fuzzy Set and RSS

The level of education determines the technology introduction level of industrial interconnection and intelligent manufacturing.Starting from web structure mining, this paper makes an in-depth study on the typical algorithm PageRank in Web Education resource structure mining. To solve the problem that PageRank algorithm only considers the link relationship between web pages and ignores the text content of web pages, which leads to drift of search results, an improved algorithm based on the distance between hyperlinked pages and reinforcement learning, disrank, is proposed. In this algorithm, the distance between education resource pages is regarded as a penalty factor to calculate the grade value of Web Education resource pages and sort them. Firstly, we use the web crawling algorithm of education resources to grab a certain number of web pages based on a certain topic as training samples, and then store them in the education resources database. Finally, PageRank algorithm and improved algorithm disrank are used to test the effectiveness of the improved algorithm..
An Examination of the Statistical Laws of Semantic Change in Clinical Notes

Natural language is continually changing. Given the prevalence of unstructured, free-text clinical notes in the healthcare domain, understanding the aspects of this change is of critical importance to clinical Natural Language Processing (NLP) systems. In this study, we examine two previously described semantic change laws based on word frequency and polysemy, and analyze how they apply to the clinical domain. We also explore a new facet of change: whether domain-specific clinical terms exhibit different change patterns compared to general-purpose English. Using a corpus spanning eighteen years of clinical notes, we find that the previously described laws of semantic change hold for our data set. We also find that domain-specific biomedical terms change faster compared to general English words.
Petrology and geochemistry of Baghche-Maryam granitoid and intermediate rocks (south Ghorveh, Kurdistan Province)

Petrology and geochemistry of Baghche-Maryam granitoid and intermediate rocks (south Ghorveh, Kurdistan Province)
PEMBUATAN PORTOFOLIO DIGITAL REPRESENTATIF PADA MAHASISWA/I PROGRAM STUDI FOTOGRAFI POLITEKTIK NEGERI MEDIA KREATIF

ABSTRACT Photography needs are now a part of daily activities, because the images that are produced can be used directly in expressing buying and selling activities and activities on new media. This phenomenon is a great opportunity for Creative Media State Polytechnic Photography Students. But the problem is that not many Photography students know the procedures for making a good or representative digital portfolio to be displayed in the online media for promotion of Photography Services. For this reason, this research has produced a representative digital portfolio for every photography student in order to increase the selling power to users of photography services both online and offline. This research uses a method with a qualitative approach. Data collection was also carried out by pretest and posttest control as a measuring tool for the success of the socialization of digital portfolio creation and literature study. The results of this study can be the basis for creating a digital portfolio as well as providing benchmarks for the marketing of Photography Services. Keywords: Photography, Digital Portofolio, new Media
Multi-Shape Free-Form Deformation Framework for Efficient Data Transmission in AR-Based Medical Training Simulators

Augmented reality medical training simulators can provide a realistic and immersive experience by overlapping the virtual scene on to the real world. Latency in augmented reality (AR) medical training simulators is an important issue as it can lead to motion sickness for users. This paper proposes a framework that can achieve real-time rendering of the 3D scene aligned to the real world using a head-mounted display (HMD). Model deformation in the 3D scene is categorised into local deformation derived from user interaction and global deformation determined by the simulation scenario. Target shapes are predefined by a simulation scenario, and control points are placed to embed the predefined shapes. Free-form deformation (FFD) is applied to multiple shapes to efficiently transfer the simulated model to the HMD. Global deformation is computed by blending a mapping matrix of each FFD with an assigned weighting value. The local and global deformation are then transferred through the control points updated from a deformed surface mesh and its corresponding weighting value. The proposed framework is verified in terms of latency caused by data transmission and the accuracy of a transmitted surface mesh in a vaginal examination (VE) training simulation. The average latency is reduced to 7 ms, less than the latency causing motion sickness in virtual reality simulations. The maximum relative error is less than 3%. Our framework allows seamless rendering of a virtual scene to the real world with substantially reduced latency and without the need for an external tracking system.
influence of sports disciplines on the development of key competencies of future physical education teachers

The reform of primary school education caused significant changes in the trajectories of the physical education. This study was aimed at identifying the ways of forming professional competencies among students as an indicator of the quality of knowledge. During the research, the following methods were used: the analysis of literature sources, laws and regulations, normative documentation, analysis, design, modeling, survey, observation, generalisation of pedagogical experience of specialists. The authors developed scientific and methodological material regarding the problem of the formation of professional competencies among students. The ways of formation of professional competencies among students were revealed. The effectiveness of the proposed approaches to the formation of professional competencies as an indicator of the quality of students’ knowledge was checked. Methodical materials and practical tasks that contain recommendations which will help teachers to create an educational environment, provide various forms of integrated learning, involve families of children in pedagogical interaction, evaluate their own practice, monitor student development were developed.
Process Evaluation on Medical Record Reporting and Information Usage Iskandar Muda Hospital Nagan Raya Regency

Medical records are all records and documents about the patient's identities, examinations, treatments, actions and other services provided to the patient. Reporting medical records at Iskandar Muda hospital still does not follow standards. This is due to the lack of discipline of officers in filling out medical records, lack of medical records of officers and related health workers, then also influenced by the Hospital Management Information System that does not yet exist. The purpose of the study was to evaluate the reporting of medical records at Sultan Iskandar Muda hospital. This study uses qualitative research. The results showed that Sultan Iskandar Muda Hospital has been processing medical record data. The procedure of making a report that is not appropriate is the completion of resumes and daily census pain hospitalization. While the proper methods are a recapitulation of outpatient visits, making reports of hospital activities and making morbidity reports of inpatients and outpatients. The medical records unit has produced internal and external reports following the guidelines, and middle-level hospital management has fully used medical record information. It can be concluded that in processing medical record data, there are some obstacles. The procedure of making a report is not following the guidelines, and medical record information has been fully utilized.
Hyperparameters optimisation for time varying signals

For the most machine learning methods, for cyclo-stationary or even stochastic signals, the performance depends critically on hyperparameters. Moreover, the tuning of more hyperparameters based on the feedback of the performance model will leak an increasingly significant amount of information about the validation set into the model. Therefore, we propose in this research two classes of hyperparameters, a general class that makes the characterization of general signal curve and the second, a specific class that define special parameters connected to the phenomena type (e.g. sensor type).
Two years with cOAlition S

With the establishment of cOAlition S we have seen for the first time a joint international approach by research funders to tackle the complex policy area of Open Access. Since the launch of Plan S in September 2018, the movement toward Open Access has gained speed and new solutions has been presented. This talk will sum up my experiences from leading the implementation work of the Plan S principles, looking back on the national and international developments we have seen over the past few years, and ahead toward the challenges that we should expect in the coming years.
Name and Subject Heading Reconciliation to Linked Open Data Authorities using Virtual International Authority File and Library of Congress Linked Data Service APIs: A Case Study featuring Emblematica Online

Libraries are actively exploring ways to use Linked Open Data (LOD) services to enhance discovery and facilitate the use of collections. Emblematica Online, which provides integrated discovery of digitized emblem books, incorporates LOD in its design. As an implementation prerequisite, the Virtual International Authority File (VIAF) and Library of Congress (LC) Linked Data Service APIs were used to reconcile name and subject strings from legacy catalog records with global authoritative links from LOD resources. This case study reports on the automated reconciliation process used and examines the efficacy of the APIs in reconciling name and subject heading entities. While a majority of strings were successfully reconciled, analysis suggests that data cleanup, rigorously consistent formatting of metadata strings, and addressing challenges in existing LOD resources and services could improve results for this corpus.
Logo Image Retrievals Using Deep Embedding Learning

A logo is s graphical emblem or mark used as an identification for a company and its products and services. Logos are legally protected as intellectual properties (IPs) if registered as trademarks (TMs). LogosTM are widely distributed online nowadays in the digital economy. Due to their wide distributions online, the constant checking of TM legal usages becomes extremely challenging in the TM registration and protection system. The fact that users can easily imitate the registered TM logo designs casts serious IP legal issue, which highlights the importance of developing an automatic logo image retrieval system. Considering the complexity of TM visual semantics, this research proposes a deep embedding learning for logo image similarity analysis using triplet-network. We propose the optimization of sampling parameters to improve the TM image retrieval performance with robust model. The research aims to reduce discrepancy between human visual interpretation. This transdisciplinary engineering research incorporates deep learning (DL) modeling and TM legal analysis for image-centric TM protection. To demonstrate the model performance, more than 10,000 images for model training and 3000 images for model testing are adopted from Logo-2K+ database. Image retrieval performance shows excellent results with recall@10 exceeding 93%.
Comprehensive Evaluation of University Teachers: Using Entropy Method

As an important part of university management and the basis of performance system, university teacher evaluation has become a research hotspot recently.However, there exist many questions in this area such as excessive subjectivity, inundate formalism and so on.All of this does not suit to the development of existing situation.Starting with the professional features of university teacher and considering the overall developing aims of university the paper design HR indexes evaluation system of university teachers from four aspects: basic quality, teaching capacity, scientific achievements and develop potential.And using information entropy-weighted method the paper constructs a human resources evaluation model of university teacher.According to the comprehensive testing coefficient we can get quantitative conclusion clearly which indicates each teacher's HR condition.Lastly combining with the demonstration of HR evaluation of management school teachers belonging to one certain university we validate the practicability and reliability of the evaluation model.The construction of evaluation model can not only help school managers evaluate teachers, but also help teachers take this as a benchmark, constantly study and explore, improve their comprehensive ability, and become excellent teachers with high quality and strong teaching and scientific research ability.
THE EFFECT OF JOURNAL WRITING TECHNIQUE ON STUDENTS’ WRITING ABILITY

This quasi experimental research aims at looking at the effect of Journal Writing technique on students’ ability in writing a paragraph. Specifically, the research answers the research questions about the students’ ability in writing, the effect of Journal Writing technique on the students’ ability in writing, and the students’ attitude toward Journal Writing technique applied in their Writing class. The sample are one class from the second semester of English Department students in 2017-2018 academic year. The data were collected through writing test and the distribution of a set of questionnaire. The results show that nearly 60% of students’ ability ini writing is at Average to Good level before the treatment. After the treatment, 56.76% of their ability is at Good to Excellent level. To test whether the increased score is statistically significant or not, the data were analyzed using t-test. Having t-obs (8.26) which is higher than t-table (2.030), it can be said that the teaching of writing using Journal Writing technique significantly effects the students’ ability in writing paragraph. The data from questionnaire support the previous findings where nearly 64% students have ‘high’ attitude toward Journal Writing technique applied in their class.