Spatiotemporal RDF Data Query Based on Subgraph Matching

Resource Description Framework (RDF), as a standard metadata description framework proposed by the World Wide Web Consortium (W3C), is suitable for modeling and querying Web data. With the growing importance of RDF data in Web data management, there is an increasing need for modeling and querying RDF data. Previous approaches mainly focus on querying RDF. However, a large amount of RDF data have spatial and temporal features. Therefore, it is important to study spatiotemporal RDF data query approaches. In this paper, firstly, we formally define spatiotemporal RDF data, and construct a spatiotemporal RDF model st-RDF that is used to represent and manipulate spatiotemporal RDF data. Secondly, we present a spatiotemporal RDF query algorithm stQuery based on subgraph matching. This algorithm can quickly determine whether the query result is empty for queries whose temporal or spatial range exceeds a specific range by adopting a preliminary query filtering mechanism in the query process. Thirdly, we propose a sorting strategy that calculates the matching order of query nodes to speed up the subgraph matching. Finally, we conduct experiments in terms of effect and query efficiency. The experimental results show the performance advantages of our approach.

Human Factors and Organizational Issues Section Synopsis IMIA Yearbook 2021

Objective: To select the best papers that made original and high impact contributions in the area of human factors and organizational issues in biomedical informatics in 2020. Methods: A rigorous extraction process based on queries from Web of Science® and PubMed/Medline was conducted to identify the scientific contributions published in 2020 that address human factors and organizational issues in biomedical informatics. The screening of papers on titles and abstracts independently by the two section editors led to a total of 1,562 papers. These papers were discussed for a selection of 12 finalist papers, which were then reviewed by the two section editors, two chief editors, and by three external reviewers from internationally renowned research teams. Results: The query process resulted in 12 papers that reveal interesting and rigorous methods and important studies in human factors that move the field forward, particularly in clinical informatics and emerging technologies such as brain-computer interfaces. This year three papers were clearly outstanding and help advance in the field. They provide examples of applying existing frameworks together in novel and highly illuminating ways, showing the value of theory development in human factors. Emerging themes included several which discussed physician burnout, mobile health, and health equity. Those concerning the Corona Virus Disease 2019 (Covid-19) were included as part of that section. Conclusion: The selected papers make important contributions to human factors and organizational issues, expanding and deepening our knowledge of how to apply theory and applications of new technologies in health.

SDN-OpenFlow Topology Discovery: An Overview of Performance Issues

Software-defined networking (SDN) is an innovative architecture that separates the control plane from the data plane to simplify and speed up the management of large networks. This means the control logic has been moved from the network hardware level to the centralized control management level. Therefore, the use of the OpenFlow Discovery Protocol (OFDP) is one of the most common protocols used to discover the network topology in a data plane and then transmit it to the control plane for management. However, OFDP has various shortcomings in its performance such as exchanging too many messages between both levels (control and data), which in turn increases the load on the SDN-Controller. Additionally, since the application layer depends entirely on the network topologies plotted in the control plane, it is very important to obtain accurate network topology information from data plane. Therefore, after providing background on topology discovery protocols to the reader, we will concentrate on performance issues. The present study identifies and discuss the primary concerns involved in the complex query process, infrastructure, influencing factors, and challenges for the topology discovery process. Furthermore, this paper will present several recent studies that have overcome and enhanced these issues. In addition, open discussion and future work concerning these issues are also discussed.

Perbandingan Performa SQL dan NoSQL Dengan PHP Pada 5 Juta Data

Dunia digital sekarang sudah merambah pada seluruh aspek kehidupan. Salah satu yang berperan penting dalam digitalisasi adalah database. Seluruh perusahaan digital pasti akan mempunyai database untuk kepentingan usaha. Semakin lama database yang dikelola akan semakin banyak, oleh karena itu kita membutuhkan aplikasi database yang ideal untuk digunakan. Pada penelitian ini, kami akan melakukan perbandingan kecepatan proses data antara SQL (MySQL) dengan NoSQL (MongoDB) dengan menggunakan VPS webserver Apache dan bahasa program PHP yang umum digunakan oleh banyak perusahaan. Metodologi yang kami gunakan adalah menguji coba kecepatan SELECT, INSERT, DELETE dan UPDATE pada jumlah data mulai 1.000, 10.000, 100.000, 1.000.000, 2.000.000 dan 5.000.000. Khusus untuk SELECT dan INSERT, kami melakukan proses looping data seperti yang umum dilakukan pada program PHP (do while). Hasil dari penelitian ini kami dapatkan bahwa proses ujicoba dengan jutaan data akan terasa lebih cepat saat menggunakan MongoDB dibanding MySQL untuk proses SELECT INSERT dan UPDATE. Namun berbeda ketika menggunakan proses DELETE, MySQL memiliki waktu respon yang lebih baik dibandingkan dengan MongoDB. Hal ini disebabkan karena MongoDB menggunakan program PHP sebagai aplikasi yang menjalankan proses query. Digital world has been impact almost every aspect of life. Database is the most important thing at digitization. All digital company will have databases. After several period of usage, the database size will improve, therefore we need to use the ideal database system. At this paper, we will compare the speed of processing data between SQL (MySQL) vs NoSQL (MongoDB) which run on VPS Apache webserver using famous PHP script. The methodology that we use for speed measurement will use SELECT, INSERT, DELETE and UPDATE at big data start from 1.000, 10.000, 100.000, 1.000.000, 2.000.000 and 5.000.000. Especially for SELECT and INSERT, we do the looping procedure that usually use at PHP script (do while). The result from this paper declare that processing million of data will be faster on MongoDB if compare with MySQL when we use SELECT, INSERT and UPDATE. However, it is different when using the DELETE process, MySQL has a better response time compared to MongoDB. This is because MongoDB uses a PHP program as an application that runs the query process.

A low-altitude public air route network for UAV management constructed by global subdivision grids

With an increasing number of unmanned aerial vehicles (UAVs), the difficulty of UAV management becomes more challenging, especially for low-altitude airspace due to complicated issues of security, privacy and flexibility. Existing management approaches to UAV flights include implementing registration of flight activity for supervision purposes, limiting the maximum flight height, setting different zones for different flight activities and prohibiting flights. In this research, we proposed a new air traffic management method for UAVs based on global subdivision theory. We designed four types of low-altitude air routes from grids, which correspond to grid sizes of 1.85 km, 128 m, 64 m and 32 m. Utilization of the subdivision grids transforms the complex spatial computation problem into a query process in the spatial database, which provides a new approach to UAV management in the fifth-generation (5G) era. We compared the number and data size of stored track records using longitude and latitude and different grid levels, computed time consumption for air route trafficability and simulated UAV flight to verify the feasibility of constructing this type of air traffic highway system. The amount of data storage and time consumption for air route trafficability can be substantially reduced by subdivision. For example, the data size using traditional expressions of latitude and longitude is approximately 1.5 times that of using a 21-level grid, and the time consumption by coordinates is approximately 1.5 times that of subdivision grids at level 21. The results of the simulated experiments indicate that in the 5G environment, gridded airspace can effectively improve the efficiency of UAV trajectory planning and reduce the size of information storage in the airspace environment. Therefore, given the increasing number of UAVs in the future, gridded highways have the potential to provide a foundation for various UAV applications.

Bibliometric Analysis of Zakat Research in Scopus Database

Scopus research paper on the zakat was systematically analyzed using the VOSviewer bibliometric measurement. A total of 492 citation data was exported from Scopus on the query of Zakat, and from the initial result, twelve journals were selected in the expanded query process. The journals are Journal of Islamic Accounting and Business Research, International Journal of Islamic and Middle Eastern Finance and Management, International Journal of Innovation Creativity and Change, Advanced Science Letters, and Iop Conference Series Earth and Environmental Science were selected in the query expansion and exported for data visualization in VOSviewer. Results from the journal query returned 492 documents specializing in research of zakat payment. Co-word or co-occurrence analysis was used to identify key themes, and potential future research direction was highlighted.

To Find Your Location: Secure and Practical Point Location Scheme

With the ubiquitous mobile devices and the advanced wireless communication, location-based service (LBS) helps people to enjoy a convenient lifestyle and has attracted numerous research interests. As a basic query process in LBS system, point location requires to find a region containing the query point. Since location belongs to sensitive information and also leads other private information leaked, it is urgent to design a secure and efficient point location scheme. In this paper, we propose a point location scheme named SecPL to protect sensitive information while supporting high efficient location query. Specifically, we introduce a LineTest scheme from asymmetric scalar-product-preserving encryption (ASPE) to facilitate the checking of whether a point lies above or below a line. Furthermore, the SecPL scheme is designed by leveraging LineTest and order-preserving encryption (OPE) scheme. Through detailed security analysis, we demonstrate that SecPL scheme achieves data privacy and query privacy at the same time. Finally, the performance evaluation demonstrates the high efficiency of the proposed SecPL scheme.

Partial Retraining Substitute Model for Query-Limited Black-Box Attacks

Black-box attacks against deep neural network (DNN) classifiers are receiving increasing attention because they represent a more practical approach in the real world than white box attacks. In black-box environments, adversaries have limited knowledge regarding the target model. This makes it difficult to estimate gradients for crafting adversarial examples, such that powerful white-box algorithms cannot be directly applied to black-box attacks. Therefore, a well-known black-box attack strategy creates local DNNs, called substitute models, to emulate the target model. The adversaries then craft adversarial examples using the substitute models instead of the unknown target model. The substitute models repeat the query process and are trained by observing labels from the target model’s responses to queries. However, emulating a target model usually requires numerous queries because new DNNs are trained from the beginning. In this study, we propose a new training method for substitute models to minimize the number of queries. We consider the number of queries as an important factor for practical black-box attacks because real-world systems often restrict queries for security and financial purposes. To decrease the number of queries, the proposed method does not emulate the entire target model and only adjusts the partial classification boundary based on a current attack. Furthermore, it does not use queries in the pre-training phase and creates queries only in the retraining phase. The experimental results indicate that the proposed method is effective in terms of the number of queries and attack success ratio against MNIST, VGGFace2, and ImageNet classifiers in query-limited black-box environments. Further, we demonstrate a black-box attack against a commercial classifier, Google AutoML Vision.

Human Factors and Organizational Issues

Objective: To select the best papers that made original and high impact contributions in the area of human factors and organizational issues in biomedical informatics in 2019. Methods: A rigorous extraction process based on queries from Web of Science® and PubMed/Medline was conducted to identify the scientific contributions published in 2019 that address human factors and organizational issues in biomedical informatics. The screening of papers on titles and abstracts independently by the two editors led to a total of 30 papers. These papers were discussed for a selection of 15 finalist papers, which were then reviewed by the two editors and by three external reviewers from internationally renowned research teams. Results: The query process resulted in 626 papers that reveal interesting and rigorous methods and important studies in human factors that move the field forward, particularly in clinical informatics and emerging technologies such as brain-computer interfaces. This year three papers were clearly outstanding and help advance the field. They provide examples of applying existing frameworks together in novel and highly illuminating ways, showing the value of theory development in human factors. Conclusion: The selected papers make important contributions to human factors and organizational issues, expanding and deepening our knowledge of how to apply theory and applications of new technologies in health.