Reviewerly/exHarmony huggingface dataset:
Perspective Chapter: Blockchain-Enabled Trusted Longitudinal Personal Health Record

In the United States, longitudinal personal health record (LPHR) adoption rate has been low in the past two decades. Patients’ privacy and security concern is a major roadblock. Patients like to control the privacy and security of their own LPHR distributed across multiple information systems at various facilities. However, little is known how a scalable and interoperable LPHR can be constructed with patient-controlled security and privacy that both patients and providers trust. As an effort to increase LPHR adoption rate and improve the efficiency and quality of care, we propose a blockchain-enabled trusted LPHR (BET-LPHR) design in which security and privacy are protected while patients have full control of the access permissions. Two limitations associated with the proposed design are discussed. Options and practical resolutions are presented to stimulate future research.
Quality Assessment of Virtual Human Assistants for Elder Users

Virtual humans (VHs) are gaining increasing attention in various fields, including games and cultural heritage and technological contexts including virtual reality and augmented reality. Recently, since VHs can simulate human-like behavior, VHs have been proposed as virtual assistants (VAs) for all sorts of education and training applications, including applications focused on the improvement of quality of life (QoL) and well-being. In this research work, we consider the quality and efficiency of VHs implemented as part of the MyHealthWatcher project, which focuses on the monitoring of health-related parameters of elder users to improve their QoL and self-management of chronic conditions. To validate our hypothesis that the increased quality of the VH has a positive effect on user satisfaction and user quality of interaction with the system, we developed and integrated into the MyHealthWatcher system two VH variations. The first was developed with mainstream technologies and the second was developed using a professional pipeline. The two variations developed were assessed by representative target users through a between-subject focus group study. The development and validation process of the two variations allowed us to draw valuable conclusions, which are discussed in this paper.
Evaluation of Private Enterprises Based on Deep Learning

In this paper, we conduct an in-depth research on the corresponding enterprises, combined with some problems existing in the process of data processing and use. We establish a deep learning model on the extensive collection and comprehensive investigation of the research results of domestic and foreign enterprises in all aspects of the process of data processing and use, and determine the research directions. Firstly, in view of the increasing complexity and dimension of enterprise data, and the difficulties of enterprise data application, this paper studies the related data preprocessing methods. Secondly, aiming at the problems of enterprise cost control and customer relationship management, this paper studies the prediction based on enterprise data through the analysis of practical problems and the processing of corresponding data. Finally, in order to progress and advance the efficiency and scientific usefulness of enterprise management, we in this paper study the evaluation based on enterprise data. The model is verified through simulations and compared with several models i.e. cross hybrid and sequential hybrid models. Using certain assumptions, the attained outcomes confirm that the accuracy of the deep learning structure of the single model is sophisticated and greater than that of the cross hybrid model, but lower than that of the sequential hybrid model.
Unsupervised Domain Adaptive Person Re-Identification Method Based on Transformer

Person re-identification (ReID) is the problem of cross-camera target retrieval. The extraction of robust and discriminant features is the key factor in realizing the correct correlation of targets. A model based on convolutional neural networks (CNNs) can extract more robust image features. Still, it completes the extraction of images from local information to global information by continuously accumulating convolution layers. As a complex CNN, a vision transformer (ViT) captures global information from the beginning to extract more powerful features. This paper proposes an unsupervised domain adaptive person re-identification model (ViTReID) based on the vision transformer, taking the ViT model trained on ImageNet as the pre-training weight and a transformer encoder as the feature extraction network, which makes up for some defects of the CNN model. At the same time, the combined loss function of cross-entropy and triplet loss function combined with the center loss function is used to optimize the network; the person’s head is evaluated and trained as a local feature combined with the global feature of the whole body, focusing on the head, to enhance the head feature information. The experimental results show that ViTReID exceeds the baseline method (SSG) by 14% (Market1501 → MSMT17) in mean average precision (mAP). In MSMT17 → Market1501, ViTReID is 1.2% higher in rank-1 (R1) accuracy than a state-of-the-art method (SPCL); in PersonX → MSMT17, the mAP is 3.1% higher than that of the MMT-dbscan method, and in PersonX → Market1501, the mAP is 1.5% higher than that of the MMT-dbscan method.
Fourteen-fold Intelligences and the Principles of Mulla Sadra’s Theology

The principles of Mulla Sadra’s theology as they relate to multiple intelligences have not been considered. Inferring multiple intelligences from Sadraean philosophy opens a new window for education focusing on transcendence-centered learning. The present essay discusses the powers of human souls as they relate to the formation of fourteen intelligences, and which are classified under five broad categories. Paying attention to the process of learning based on distinct types of intelligences sets the stage for designing a consistent educational program ensuring both worldly and other worldly happiness.
Performance Evaluation of Query Plan Recommendation with Apache Hadoop and Apache Spark

Access plan recommendation is a query optimization approach that executes new queries using prior created query execution plans (QEPs). The query optimizer divides the query space into clusters in the mentioned method. However, traditional clustering algorithms take a significant amount of execution time for clustering such large datasets. The MapReduce distributed computing model provides efficient solutions for storing and processing vast quantities of data. Apache Spark and Apache Hadoop frameworks are used in the present investigation to cluster different sizes of query datasets in the MapReduce-based access plan recommendation method. The performance evaluation is performed based on execution time. The results of the experiments demonstrated the effectiveness of parallel query clustering in achieving high scalability. Furthermore, Apache Spark achieved better performance than Apache Hadoop, reaching an average speedup of 2x.
Comparative Analysis on the Effect of Surface Reflectance for Laser 3D Scanner Calibrator

The calibrator is one of the most important factors in the calibration of various laser 3D scanning instruments. The requirements for the diffuse reflection surface are emphasized in many national standards. In this study, spherical calibrator and plane calibrator comparative measurement experiments were carried out. The black ceramic standard sphere, white ceramic standard sphere, metal standard sphere, metal standard plane, and white ceramic standard plane were used to test the laser 3D scanner. In the spherical calibrator comparative measurement experiments, the results indicate that the RMS of the white ceramic spherical calibrator with a reflectance of approximately 60% is 10 times that of the metal spherical calibrator with the reflectance of approximately 15%, and the RMS of the black ceramic spherical calibrator with reflectance of approximately 11% is of the same order as the metal spherical calibrator. In the plane calibrators comparative measurement experiments, the RMS of the flatness measurement is 0.077 mm for the metal plane calibrator with a reflectance of 15%, and 2.915 mm for ceramic plane calibrator with a reflectance of 60%. The results show that when the optimal measurement distance and incident angle are selected, the reflectance of the calibrator has a great effect on the measurement results, regardless of the outlines or profiles. Based on the experiments, it is recommended to use the spherical calibrator or the standard plane with a reflectance of around 18% as the standard, which can obtain reasonable results. In addition, it is necessary to clearly provide the material category and surface reflectance information of the standard when calibrating the scanner according to the measurement standard.
Variable-Scale Visualization of High-Density Polygonal Buildings on a Tile Map

To better satisfy user’s needs for the accurate visualization of massive amounts of geographic data, the variable-scale expression of map content based on multilevel data organization has attracted increasing attention. Traditional methods based on vector data usually cannot handle tile data in the form of a grid on the network. Therefore, this paper proposes a variable-scale visualization method for high-density buildings based on a raster tile map. First, the buildings on a tile map are typified on the basis of linear spectral clustering (LSC) superpixel segmentation to reduce the number of buildings. Then, the shapes of buildings are simplified using the minimum bounding rectangle method. Lastly, the designed focus + glue + context (F + G + C) variable-scale model is used for visual output. The OpenStreetMap tile data are used to perform experiments. Compared with traditional methods, the proposed variable-scale visualization method in this paper considers the spatial distribution, quantity, and shape characteristics of buildings, reduces the clutter of data, and has a better (average value of building quantity, area and density is 57%) visual effect. Variable-scale visualization can be applied to unstructured map data sources and extended to grid data sources to improve the readability and recognizability of high-density buildings.
The Potential of Information and Communication Technologies to Generate International Trade in Africa

This article employs the dynamic panel two-step system generalised method of moments (GMM) approach to investigate the effects of information and communication technology (ICT) on trade and economic growth at a multisectoral level in 38 African countries from 1990 to 2019. The study reveals a significant and positive relationship between ICT and the export of agricultural raw materials and services. ICT shows a negative relationship with import in the agricultural sector, and a positive and significant relationship within the manufacturing sector. Additionally, there is no evidence of statistically significant relationships between ICT and service import. In relating ICT to growth, at the sectoral level, significant positive effects on growth were found with a varying magnitude in all sectors. The national ICT recommendation is that governments in African countries should increase investment in the ICT sector of the economy, which will have a remarkable effect on international trade and the economy.
Power-Law Dynamic Arising from Machine Learning

We study a kind of new SDE that was arisen from the research on optimization in machine learning, we call it power-law dynamic because its stationary distribution cannot have sub-Gaussian tail and obeys power-law. We prove that the power-law dynamic is ergodic with unique stationary distribution, provided the learning rate is small enough. We investigate its first exist time. In particular, we compare the exit times of the (continuous) power-law dynamic and its discretization. The comparison can help guide machine learning algorithm.
Comparison of the RCA Between China and KOR: From the Perspective of Value-Added

Purpose - This paper empirically explores the RCA of electrical equipment trade between China and Korea from the perspective of gross trade and value-added trade. The goal of this paper is to scan the electrical equipment's RCA, the decomposition of gross exports, and the impacts of an exerted shock.&#x0D; Design/methodology - We applied the domestic value-added method in measuring the RCA, which could be more accurate than traditional RCA since it excludes foreign value-added. Based on the research purpose, this paper follows the framework of Koopman, Wang, and Wei (2014)—as extended by Wang, Wei, and Zhu (2018). It extracts the data from the 2019 Multi-regional Input-Output (MRIO) databases compiled by the Asian Development Bank in January 2021.&#x0D; Findings - After rigorous examination, the main findings are as follows: First, the electrical equipment sector maintains a consistent comparative advantage in either assessing method. Second, China exports more gross goods of electrical equipment to the world than South Korea does, but there is a trade deficit with Korea. Third, South Korea and P.R. China are the most significant bilateral partners of foreign value-added sourcing. Finally, it is surprising that there is a shock on electrical equipment; the partner’s service, as well as manufacturing sectors, would be affected.&#x0D; Originality/value - This paper explores the revealed comparative advantage between Korea and China from traditional gross export and value-added perspectives. Second, we apply the information from the 2019 MRIO database compiled by the Asian Development Bank in January 2021, reflecting the current situation. Third, this paper analyzes the electrical equipment and the impacts on other parties’ sectors. Finally, we carry out the subjects that deserve to be investigated in the future.
Systematic Literature Review: Grammarly as a Medium in Analyzing Grammar for University Students

Nowadays, the rapid growth of technologies brings out the educational learning application or web. One example of educational technology is the automatic online grammar checker, Grammarly. Grammarly is an online application that is used to scan documents for grammar checkers and plagiarism checkers. It provides suggestions on all forms of corrective vocabulary and sentence or rephrasing suggestions. Besides, Grammarly also includes the correct word and provide several alternatives and identify possible misspellings of the word. Researchers used the systematic literature review as the method of the research. This systematic literature review aims to explore on how Grammarly as a medium for analyzing grammar is used in the process of the analysis. The researchers are interested to review the literature on Grammarly as a medium for analyzing grammar. Moreover, researchers attempt to look at the effectiveness of Grammarly on learning activities. Researchers found 35 journal articles that are eligible for the analysis. The result showed that the presence of Grammarly had been identified to be a good learning assistance and useful to use for students. Meanwhile, in the implementation of the application, Grammarly has a lot of room for improvement to be made in this application.
Improving English Speaking Skill Through Video Call Conversation

Information and communication technology (ICT) has developed so rapidly and become an inseparable aspect of human life. The development of information and communication technology (ICT) has been used by many people to facilitate and help human activities, including in the educational aspect. Nowadays, many teachers and educators use technology to help them to deliver and to transfer teaching materials to students. One of the most frequently used technologies today is video call (VC) which is a means of communication where a person can communicate directly by looking at the other person. Therefore, this study aims to see the improvement of students' speaking skills in English when using video call conversation (VCC) as one of the learning media. The method used in this research is mix method. The research data was obtained by giving speaking test and questionnaires to 35 students who took English classes, then interviews about the use of video call conversations were conducted with 15 selected students. The results shows that students experienced increased confidence when speaking English by using video call conversation (VCC) when compared to not using video call conversation (VCC). Then, students feel more interested and comfortable speaking in English when using video call conversations (VCC).
The Effectiveness of Instagram as a Medium to Develop Vocabulary Competence in Senior High School: a Systematic Literature Review

Social media has big impact on daily life, which indirectly makes people change cultural mindset to modern perception. One of social media is Instagram, which this application used to build relationship between peoples through virtual communication and long-distance interactions efficiently. Educators and researchers often apply it in global contexts for educational purposes, such as teaching and learning English vocabulary. When talk about English Learning, basically vocabulary become important aspect to measure understanding and know the level of English aspects. Combining Instagram with learning English is effective way to increase many benefits, especially for students. This article attempts to address about how effective of Instagram as Medium to Develop Vocabulary Competence through Systematic Literature Review Method in senior high school level. The type of research is Systematic Literature Review method. Systematic Literature Review method is method of research that use to identify, study, review, evaluate, and interpret all available research. Related with that, this method refers to topic interest to some phenomenon with certain relevant research questions. Instagram give benefits to develop student quality of understanding meaning many words. In that context, Instagram become one of medium to improve student-efficacy to get better vocabularies knowledge and reach information in same time.
Model Aplikasi Peminjaman Ruangan Berbasis Web Pada Tingkat Fakultas di Perguruan Tinggi

&lt;p&gt;&lt;em&gt;The procedure for borrowing a room which is still done manually at the faculty level in Higher Education causes the borrowing process to be inefficient, because all matters must go to the service officer directly. The research aims to develop a Web-based application model that can be used in the process of borrowing rooms at faculty level managers in universities, without having to go to service officers, so that the borrowing process becomes more effective and efficient. Application development uses the SDLC (Software Development Life Cycle) method. The case study was conducted at the Faculty of Economics and Business, Udayana University. The system modeling uses structured modeling tools, while the system construction uses the PHP programming language, JavaScript, and MySQL database. The main functional features identified at the requirements analysis stage are the system's ability to provide an online room loan interface, room loan statistics, and room loan reports for faculty management. The results of the functional test using Blackbox Testing show that all functional features available in the application have functioned validly.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Keywords: Software; Software Development Life Cycle; Functional testing; Black box testing&lt;/em&gt;&lt;/p&gt;&lt;p align="center"&gt;&lt;strong&gt; &lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Abstrak.&lt;/strong&gt; Prosedur peminjaman ruangan yang masih dilakukan secara manual pada tingkat fakultas di perguruan tinggi menyebabkan proses peminjaman menjadi tidak efisien, karena segala urusan harus mendatangi petugas pelayanan secara langsung. Penelitian bertujuan mengembangkan model aplikasi berbasis &lt;em&gt;web&lt;/em&gt; yang dapat digunakan dalam proses peminjaman ruangan pada pengelola tingkat fakultas di Perguruan Tinggi, tanpa harus mendatangi petugas pelayanan, sehingga proses peminjaman menjadi lebih efektif dan efisien. Pengembangan aplikasi menggunakan metode SDLC (&lt;em&gt;Software Development Life Cycle)&lt;/em&gt;. Studi kasus dilakukan pada Fakultas Ekonomi dan Bisnis Universitas Udayana. Pemodelan sistem menggunakan &lt;em&gt;tools&lt;/em&gt; pemodelan terstruktur, sedangkan konstruksi sistem menggunakan bahasa pemrograman &lt;em&gt;PHP, JavaScript&lt;/em&gt;, dan basis data&lt;em&gt; MySQL&lt;/em&gt;. Fitur fungsional utama yang diidentifikasi pada tahap analisis kebutuhan berupa kemampuan sistem menyediakan antarmuka peminjaman ruangan secara &lt;em&gt;online&lt;/em&gt;, data statistik peminjaman ruangan, serta laporan peminjaman ruangan bagi manajemen Fakultas. Hasil uji fungsional menggunakan &lt;em&gt;Black box testing&lt;/em&gt; menunjukkan seluruh fitur fungsional yang tersedia pada aplikasi telah berfungsi secara valid.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Kata kunci&lt;/strong&gt;&lt;strong&gt;:&lt;/strong&gt;&lt;em&gt; Perangkat lunak; Software Development Life Cycle; Uji fungsional; Black box testing &lt;/em&gt;&lt;/p&gt;
Attention-guided cross-modality person re-identification

Cross-modality person re-identification, also known as RGB-infrared person re-identification, is a person recognition and retrieval technology between visible and infrared images. As an essential technologies of video intelligent surveillance system, the technology is urgently needed in security monitoring and suspect tracking. The modality discrepancy and intra-class variations in cross-modality person re-identification make it difficult to extract effective discriminable features of person identity. There are significantly fewer effective discriminable features in the shared feature space caused by shared network parameters. In order to solve this problem, an attention-guided cross-modality person re-identification is designed in this paper. The attention module uses the attention mechanism to focus on the salient features, so as to guide the network to put more parameters on the learning of salient features, so that the network can learn more discriminable, features from salient features. A comparative experiment on two standard data sets of cross-modality person re-identification verifies the effectiveness and advancement of the proposed method. For example, the proposed method improves rank-1 by 17.79% on SYSU-MM01 and 16.55% on mAP.
Pose guided adaptive graph convolutional network based on pose for obscured pedestrian re-identification

In the Reid method which is based on deep learning, the combination of local features and global features can provide a robust representation for person retrieval. Human pose information can provide the location of the human skeleton, thus effectively directing the network to focus more on these critical regions, while also helping to reduce noise interference from background or occlusion. However, previous pose based approaches may not take full advantage of the pose information and rarely consider the different contributions of independent local features. In this paper, we design a pose guided multi-branch graph convolutional attention network (PG-MBGCAN) for the problem of re-identification of occluded pedestrians, which exploits the pose relationship to improve the robustness of pedestrian features and considers the contributions of different local features. Experimental results show that the proposed method in this paper has good performance in different datasets.