Reviewerly/exHarmony huggingface dataset:
Quantum-enhanced angle-of-arrival pre-estimation of radio-frequency signals

Quantum metrology with quantum effects, gives remarkable possibility to increase the precision of estimated parameter. Here, we demonstrate a quantum-enhanced angle-of-arrival pre-estimation protocol, which conduces to predict a target orientation for modern phased-array radar and sonar systems. Taking edge sensor as reference, we estimate the first, second, and third derivatives of radio-frequency (RF) phase via only four-sensor network arranged in linear topology. Combining the quantum technology with high-order derivatives, the receiving angle-of-arrival at arbitrary sensor can be pre-estimated with enhanced sensitivity of nearly 49.5%.
Looming market failure in cloud computing: a new institutional economics perspective

Purpose In recent times, high demand for cloud-based services has led to substantial focus in extant literature from technological and business perspectives. However, the prevailing market imperfections have not drawn much interest. This study aims to emphasize on potential sources of market imperfections from new institutional economics (NIE) perspective and attempts to bring forth the importance of public policy in cloud computing ecosystem. Design/methodology/approach This study takes a review-based deductive approach to present a set of propositions which highlight potential causes leading to suboptimal performance of cloud-based services. Findings Lack of clarity around ownership and property rights, high asset specificity, existence of information asymmetry and bounded rationality of the provider and consumer, lead to higher transaction cost for providers and consumers, discouraging participation. This would lead to moral hazard and adverse selection and create market imperfections. Appropriate contractual guidelines, standards, legal framework and policy measures will reduce the risk of such imperfections. Research limitations/implications As the focus of the study is to forward the propositions and not to empirically test them, future researchers can adopt data-driven studies to validate those propositions. Practical implications To ensure equity in the cloud-market, government and industry bodies should work towards enabling both the small and large players to use cloud-based services efficiently and effectively. Appropriate public policy measures can help remove potential market imperfections, encourage better participation and adoption of cloud-based services. Originality/value This study identifies potential market imperfections in cloud computing ecosystem through the lens of the theoretical frameworks of NIE.
Motion Tracker Beta: A GUI based open-source motion tracking application

Motion tracking is a widely used image processing technique, where the goal is to follow and register the movement of specified objects over time, from video recordings. Thanks to the development of optical devices and tracking algorithms, the popularity of the method among researchers is continuously growing in a rich area of applications. Despite the interest, there is currently no free and open-source motion tracking software, which can satisfy the growing demands of the scientific community for engineering applications. This paper introduces Motion Tracker Beta: a GUI based open-source motion tracking application. With multiple implemented tracking algorithms, the possibility of multi-object, rotation or size change tracking and a diverse set of numerical differentiation methods for velocity and acceleration calculations, the aim of the software is to facilitate motion analysis in various research areas. The software and the source code are available at https://github.com/flochkristof/motiontracker.
A multi-case induction adaptation study of tacit knowledge based on NRS and CBR

Purpose This study aims to deal with the case adaptation problem associated with continuous data by providing a non-zero base solution for knowledge users in solving a given situation. Design/methodology/approach Firstly, the neighbourhood transformation of the initial case base and the view similarity between the problem and the existing cases will be examined. Multiple cases with perspective similarity or above a predefined threshold will be used as the adaption cases. Secondly, on the decision rule set of the decision space, the deterministic decision model of the corresponding distance between the problem and the set of lower approximate objects under each choice class of the adaptation set is applied to extract the decision rule set of the case condition space. Finally, the solution elements of the problem will be reconstructed using the rule set and the values of the problem's conditional elements. Findings The findings suggest that the classic knowledge matching approach reveals the user with the most similar knowledge/cases but relatively low satisfaction. This also revealed a non-zero adaptation based on human–computer interaction, which has the difficulties of solid subjectivity and low adaptation efficiency. Research limitations/implications In this study the multi-case inductive adaptation of the problem to be solved is carried out by analyzing and extracting the law of the effect of the centralized conditions on the decision-making of the adaptation. The adaption process is more rigorous with less subjective influence better reliability and higher application value. The approach described in this research can directly change the original data set which is more beneficial to enhancing problem-solving accuracy while broadening the application area of the adaptation mechanism. Practical implications The examination of the calculation cases confirms the innovation of this study in comparison to the traditional method of matching cases with tacit knowledge extrapolation. Social implications The algorithm models established in this study develop theoretical directions for a multi-case induction adaptation study of tacit knowledge. Originality/value This study designs a multi-case induction adaptation scheme by combining NRS and CBR for implicitly knowledgeable exogenous cases. A game-theoretic combinatorial assignment method is applied to calculate the case view and the view similarity based on the threshold screening.
Professional Development in Certificate Educational Studies Leadership (CESL) for School Literacy Movement

The purpose of this research is to analyze the improvement of the professional competencies of teachers who participated in the "Certificate in Educational Studies in Leadership (CESL)â€ for literacy movement at Tugu Utara 19 primary school. Researchers in this study used a qualitative approach with descriptive methods aimed at telling a story of a data, event or phenomenon unearthed through in-depth interviews with sources with knowledge and understanding and deep experience of the phenomenon. Data collection techniques use observation, interview, and documentation techniques. The results showed that the competence of professional teachers in carrying out literacy was a cognitive pre-action literacy movement in schools, 83.3% very good which answered almost 80% of teachers and educational personnel that they liked literacy corridors, and as many as 87.5%, which is 87.5% answering very happy, suggestions and upgrades to the next school project at Tugu Utara 19 primary school.
Design of Web-Based Management Information System for Student Organizations in Kendal Regency Using Next.js Framework

Regional student organizations are essential for student development and fostering regional peer relationships. However, regional student organizations faced challenges in management due to the lack of digitization such as in the approval of proposals, submission of work programs, and accountability reports. With these challenges, the development of information systems was essential for simplifying regional student organization management and increasing member participation and involvement. This research focused on the information system design stage, which includes database design and interface design where the goal is to design an information system for Kendal area student organizations using Node.js technology and Next.js frameworks that use the System Development Life Cycle with a waterfall model for the research method. Next.js is a popular framework that simplified web application development with server-side rendering and static site generation, enhancing system performance and reliability. In conclusion, the design of a Web-Based Management Information System for Student Organizations in Kendal Regency using the Next.js framework successfully incorporated various system components, including Unified Modelling Language diagrams, Entity-Relationship Diagrams, system architecture, and user interface design. Future research should focus on the development and implementation of the proposed system to further improve the management of student organizations in Kendal District.
Development of Website Based Jobdesk Document Management System Using Agile Method at PT. Pupuk Kujang

Ineffective storage and not recorded neatly are the reasons for making this system. Taking the name Jobdesk itself was chosen because it is a system that aims to make it easier for employees to send Jobdesk document information and can help the input process digitally. This system is also made not limited only to admins and employees, admins can also create new users and give access to the employees who have positions related to this application. This system has been implemented in accordance with the request from the development department and organization of PT Pupuk Kujang. This system is made based on a website using php language with CodeIgniter 3 framework
Scoping review of the hardware and software features of virtual reality exposure therapy for social anxiety disorder, agoraphobia, and specific phobia

Introduction: The use of virtual reality technology to deliver exposure therapy in the treatment of phobic anxiety (i.e., social anxiety disorder, agoraphobia, and specific phobia) has been proposed to be advantageous compared with in-vivo exposure therapy. These supposed advantages depend on the features of the virtual reality technology and how it is used therapeutically. Therefore, the aim of this study was to provide a comprehensive overview of the features of the hardware and software used in studies examining virtual reality exposure therapy studies for phobic anxiety disorders. Methods: 70 studies using virtual reality exposure therapy to treat social anxiety disorder, agoraphobia and/or specific phobia, were systematically reviewed for 46 data points relating to these features. Results: We found that studies generally did not utilize contemporary virtual reality technology and that hardware and software features were inconsistently delineated. Discussion: The implications of these findings are that the use of modern virtual reality technology represents a relevant frontier in anxiety treatment and that a framework for reporting technical features of virtual reality exposure interventions would benefit the field.
Information System for Forecasting Course Quotas using Trend Analysis Method

Determining the class quota at each period of filling out the KRS (Study Plan Card) at the beginning of the semester is often an activity that cannot be determined easily. This is due to several important factors in it, one of the most influential and difficult things is the uncertainty when determining the quota for the number of students who will take the course in question, if later there is an error in predicting the number of students who will take the course, then the class quota that is prepared will certainly be less so that it leads to the disruption of the ongoing Student KRS registration process. The method used in this study is forecasting using trend analysis which aims to determine how much capacity or inventory is needed for decision-making, then a system will be designed that can be used to predict the number of forecasting quotas for courses that will be provided. The system design applies the system development method with UML. The stages of the process are carried out from collecting and processing subject offer quota data several previous academic years. Research has succeeded in building a model to make predictions using the Trend Analysis method, so that it can be used as a recommendation for the number of quotas offered for the next academic year.
Adaptive Model for Industrial Systems Using Echo State Networks

When a model of an industrial system is developed, it is expected that this model performs consistently when applied to other identically designed systems. However, different operating hours, degradation or maintenance, among other circumstances, cause a change in the dynamics of the system and result in the model not performing as expected. For this reason, it is necessary to build a model that continuously adapts to changes in the dynamics of the system, in order to handle such deviations and thus reduce the estimation error. This paper proposes the development of an adaptive model based on Echo State Networks to estimate the level of a water tank. For this purpose, two identically designed industrial pilot plants are used, taking one of them as a reference for the parameterization, training and validation of the model, and applying the developed model to the other one in order to evaluate the adaptation to changes in the dynamics of the system.
Mapping the international ecosystem of national health data spaces. A scoping review protocol

<ns3:p><ns3:bold>Background: </ns3:bold>The reuse of participant-level health data by public health and surveillance institutions, hospitals, doctors, and patients is an emerging priority for a number of national governments. Technical and semantic interoperability of health data ecosystems is important for detecting and responding to global health challenges, including emerging infectious diseases, antimicrobial resistance, and vaccine-preventable illnesses. In this scoping review, we will identify and describe health data ecosystems, spaces, clouds, and commons, national-level mechanisms for enabling the reuse of participant-level health data.</ns3:p><ns3:p> <ns3:bold>Methods and analysis: </ns3:bold>We will apply the Arskey and O’Malley scoping review approach to describe governance, content, and semantic and technical interoperability of data and metadata in national health data ecosystems. We selected a scoping rather than a systematic review methodology to provide a high-level analysis of the current state of health data ecosystems’ implementation of the FAIR principles for data resources. The systematic search strategy was pilot tested and tailored for Ovid(Medline), CINAHL, and Web of Science. We will also conduct web scraping and consult stakeholders to identify additional health data ecosystems. Two reviewers will conduct the title-abstract and full-text screening and data charting independently. Discrepancies will be resolved by consensus, and results will be summarized in narrative form.</ns3:p><ns3:p> <ns3:bold>Ethics and dissemination: </ns3:bold>Ethical approval is not required for this scoping review of published studies and grey literature. The scoping review protocol was registered prior to initiating the search strategy. Study results will be submitted for publication in an Open Access journal.</ns3:p>
Numerical Analysis of the Diversity of Keyboard Instrument Playing Fingerings

Abstract Fingering is the foundation of keyboard instrument performance and an important part of keyboard music, but few people pay attention to its development. The evolution from the early variety of playing fingerings to the thumb-centered five-fingerings is even less mentioned. At present, steganographic analysis mainly focuses on the diversity and high dimensionality of features. Faced with the emerging new steganography, it is difficult for a single feature to cover and express the influence of steganography process on the multi-dimensional distribution of images. Therefore, it is necessary to combine various features through certain methods to analyze the changes of image properties before and after steganography embedding in a larger range and more types. The experimental results show that the experimental comparison diagram of Comb-RichModel based on diversity features and other steganographic analysis algorithms can be seen by replacing filtering and adding SPAM features. Compared with numerical analysis, the detection accuracy of the Comb-RichModel with diversified features has been improved to some extent, and its detection performance has improved stably from low embedding rate to high embedding rate. It is proved that the numerical analysis can effectively analyze the diversity characteristics of keyboard instrument playing fingerings.
CUDAS: Distortion-Aware Saliency Benchmark

Visual saliency prediction remains an academic challenge due to the diversity and complexity of natural scenes as well as the scarcity of eye movement data on where people look in images. In many practical applications, digital images are inevitably subject to distortions, such as those caused by acquisition, editing, compression or transmission. A great deal of attention has been paid to predicting the saliency of distortion-free pristine images, but little attention has been given to understanding the impact of visual distortions on saliency prediction. In this paper, we first present the CUDAS database - a new distortion-aware saliency benchmark, where eye-tracking data was collected for 60 pristine images and their corresponding 540 distorted formats. We then conduct a statistical evaluation to reveal the behaviour of state-of-the-art saliency prediction models on distorted images and provide insights on building an effective model for distortion-aware saliency prediction. The new database is made publicly available to the research community.
Intelligent Medical Knowledge Robot Based on Knowledge Graph

Abstract Artificial intelligence has been gradually integrated into life, and knowledge graph is also particularly important, and its application is gradually maturing. In recent years researchers have used the rich entity and relationship information in the knowledge graph to overcome many difficulties. Through the fusion, reasoning, and deep learning of large-scale knowledge graphs, knowledge graphs link and apply these memories to generate wisdom. It can be said that knowledge graph has become the infrastructure of the era of artificial intelligence. The article combines Neo4j with ECharts visualization to develop a visual question answering robot in the medical field. This uses a more scientific method to understand and present data, provides a humanized visual question answering robot. And finally shows the effect of visual knowledge graph as well as assists users in the analysis of specific diseases.
Development of Non Hosted Custom Domain Websites As a Learning Medium to Improve Learning Outcomes

Learning media plays an important role in the learning process, especially in concrete courses. The use of easy, dynamic and interesting media can have an effect on students to learn compared to boring conventional learning media so that it is necessary to develop new media that can overcome these problems. The purpose of this study is to determine the feasibility and effectiveness of learning media in the form of non-hosted custom domain websites to improve learning outcomes. This research uses a research and development method with a 5-stage ADDIE development model. In the results of the feasibility test, media experts obtained a score with a percentage of 81.33% with a very decent category, while material experts obtained a score with a percentage of 89.33% with a very decent category. The results of the trial on 25 graduate students obtained a percentage of 92% with a very decent category. The increase in learning outcomes above KKM 75 after using non-hosted custom websites reached 84% from the previous 20% so that it can be concluded that the use of non-hosted custom domain websites on learning media can improve learning outcomes. The new findings in this study are in the form of the use of websites that are usually used paid for education, now it is easier and cheaper to use non-hosted websites that are custom domains using the teacher's own name, so that the use of the teacher's name can increase credibility in the world of education, especially in cyberspace. Keywords: Learning Media, Non hosted Website, Improve Learning Outcome
dsSurvival 2.0: privacy enhancing survival curves for survival models in the federated DataSHIELD analysis system

Survival models are used extensively in biomedical sciences, where they allow the investigation of the effect of exposures on health outcomes. It is desirable to use diverse data sets in survival analyses, because this offers increased statistical power and generalisability of results. However, there are often challenges with bringing data together in one location or following an analysis plan and sharing results. DataSHIELD is an analysis platform that helps users to overcome these ethical, governance and process difficulties. It allows users to analyse data remotely, using functions that are built to restrict access to the detailed data items (federated analysis). Previous works have provided survival modelling functionality in DataSHIELD (dsSurvival package), but there is a requirement to provide functions that offer privacy enhancing survival curves that retain useful information.We introduce an enhanced version of the dsSurvival package which offers privacy enhancing survival curves for DataSHIELD. Different methods for enhancing privacy were evaluated for their effectiveness in enhancing privacy while maintaining utility. We demonstrated how our selected method could enhance privacy in different scenarios using real survival data. The details of how DataSHIELD can be used to generate survival curves can be found in the associated tutorial.
Analysis of bridge foundation pile detection based on convolutional neural network model

Abstract In order to quickly and accurately detect the instability of foundation piles on concrete Bridges, an improved convolutional neural network based image recognition method for concrete bridge pile foundations was proposed. In order to improve the image quality, the entropy threshold method is used to process the image, and the two-channel convolutional neural network is designed to extract the image features fully. The improved traditional Relu activation function avoids model underfitting. Support vector machine (SVM) was used to replace Softmax classifier to improve computing efficiency. The experiment of bridge pile foundation image recognition shows that the improved convolutional neural network has significantly improved the recognition rate of the real bridge pile foundation. No matter how many degrees the image is rotated, the method in this article always maintains a high recognition rate, and the recognition rate does not fluctuate much, indicating that the algorithm in this article has good robustness to rotation and translation. In summary, the average recognition rate of the 5 groups was 96.26%. The feasibility of this method in identifying bridge pile foundation is proved.