Parallel Processing Strategies for Geospatial Data in a Cloud Computing Infrastructure

This paper is on the optimization of computing resources to process geospatial image data in a cloud computing infrastructure. Parallelization was tested by combining two different strategies: image tiling and multi-threading. The objective here was to get insight on the optimal use of available processing resources in order to minimize the processing time. Maximum speedup was obtained when combining tiling and multi-threading techniques. Both techniques are complementary, but a trade-off also exists. Speedup is improved with tiling, as parts of the image can run in parallel. But reading part of the image introduces an overhead and increases the relative part of the program that can only run in serial. This limits speedup that can be achieved via multi-threading. The optimal strategy of tiling and multi-threading that maximizes speedup depends on the scale of the application (global or local processing area), the implementation of the algorithm (processing libraries), and on the available computing resources (amount of memory and cores). A medium-sized virtual server that has been obtained from a cloud service provider has rather limited computing resources. Tiling will not only improve speedup but can be necessary to reduce the memory footprint. However, a tiling scheme with many small tiles increases overhead and can introduce extra latency due to queued tiles that are waiting to be processed. In a high-throughput computing cluster with hundreds of physical processing cores, more tiles can be processed in parallel, and the optimal strategy will be different. A quantitative assessment of the speedup was performed in this study, based on a number of experiments for different computing environments. The potential and limitations of parallel processing by tiling and multi-threading were hereby assessed. Experiments were based on an implementation that relies on an application programming interface (API) abstracting any platform-specific details, such as those related to data access.

An Education Process Mining Framework: Unveiling Meaningful Information for Understanding Students’ Learning Behavior and Improving Teaching Quality

This paper focuses on the study of automated process discovery using the Inductive visual Miner (IvM) and Directly Follows visual Miner (DFvM) algorithms to produce a valid process model for educational process mining in order to understand and predict the learning behavior of students. These models were evaluated on the publicly available xAPI (Experience API or Experience Application Programming Interface) dataset, which is an education dataset intended for tracking students’ classroom activities, participation in online communities, and performance. Experimental results with several performance measures show the effectiveness of the developed process models in helping experts to better understand students’ learning behavioral patterns.

Streamlining statistical reproducibility: NHLBI ORCHID clinical trial results reproduction

Reproducibility in medical research has been a long-standing issue. More recently, the COVID-19 pandemic has publicly underlined this fact as the retraction of several studies reached out to general media audiences. A significant number of these retractions occurred after in-depth scrutiny of the methodology and results by the scientific community. Consequently, these retractions have undermined confidence in the peer-review process, which is not considered sufficiently reliable to generate trust in the published results. This partly stems from opacity in published results, the practical implementation of the statistical analysis often remaining undisclosed. We present a workflow that uses a combination of informatics tools to foster statistical reproducibility: an open-source programming language, Jupyter Notebook, cloud-based data repository, and an application programming interface can streamline an analysis and help to kick-start new analyses. We illustrate this principle by (1) reproducing the results of the ORCHID clinical trial, which evaluated the efficacy of hydroxychloroquine in COVID-19 patients, and (2) expanding on the analyses conducted in the original trial by investigating the association of premedication with biological laboratory results. Such workflows will be encouraged for future publications from National Heart, Lung, and Blood Institute-funded studies.

basicsynbio and the BASIC SEVA collection: Software and vectors for an established DNA assembly method

Standardized DNA assembly methods utilizing modular components provide a powerful framework to explore design spaces and iterate through Design-Build-Test-Learn cycles. Biopart Assembly Standard for Idempotent Cloning (BASIC) DNA assembly uses modular parts and linkers, is highly accurate, easy to automate, free for academic and commercial use, while enabling simple hierarchical assemblies through an idempotent format. These attributes facilitate various applications including pathway engineering, ribosome binding site tuning, fusion protein synthesis and multiplex gRNA expression. In this work we present basicsynbio, an open-source software encompassing a Web App (https://basicsynbio.web.app/) and Python Package (https://github.com/LondonBiofoundry/basicsynbio). With basicsynbio, users can access commonly used BASIC parts and linkers while robustly designing new parts and assemblies with exception handling for common design errors. Furthermore, users can export sequence data and create build instructions for manual or automated workflows. The generation of build instructions relies on the BasicBuild Open Standard which is easily parsed for bespoke workflows and is serialised in Java Script Object Notation for transfer and storage. We demonstrate basicsynbio by assembling a collection of 30 BASIC-compatible vectors using various sequences including modules from the Standard European Vector Architecture (SEVA). The BASIC SEVA collection encompasses plasmids containing six antibiotic resistance markers and five origins of replication from different compatibility groups, including a temperature-sensitive variant. We deposit the collection on Addgene under an OpenMTA agreement, making them available. Furthermore, these sequences are accessible from within the basicsynbio application programming interface along with other collections of parts and linkers, providing an ideal environment to design BASIC DNA assemblies for bioengineering applications.

PROGRAM APLIKASI PEMBELAJARAN PEMROGRAMAN JAVA YANG ATRAKTIF BERBASIS ANDROID

Di Fakultas Ilmu Komputer (FILKOM) Universitas Brawijaya, hasil review menunjukkan bahwa 76% dari 100 mahasiswa FILKOM lebih tertarik pada materi pembelajaran selain mata kuliah pemrograman esensial. Keterbatasan sumber materi yang diperoleh dan pemanfaatan teknik Student Centered Learning di FILKOM dinilai kurang mengakomodir mahasiswa untuk memahami materi pembelajaran. Dengan cara ini, kerangka pembelajaran pemrograman java elektronik yang memikat telah dibuat dengan memanfaatkan teknik gamifikasi. Bagaimanapun, penelitian dari Baidu Study mengungkapkan bahwa klien aplikasi serbaguna 97% lebih besar dari program yang hanya 76%. Beberapa penelitian terkait gamification juga mengungkapkan bahwa judul eksplorasi tambahan adalah sejauh portabilitas. Mengingat informasi ini, penting untuk mengembangkan aplikasi pembelajaran pemrograman Java dalam bentuk serbaguna yang berjalan sebagai pelanggan, sehingga kerangka kerja saat ini dapat berfungsi sebagai server. Dalam pengujian ini, aplikasi berbasis pada tahap android lokal. Untuk bertukar informasi dengan server, penting untuk membuat administrasi web yang digunakan sebagai Application Programming Interface (API). Hasil pengembangan aplikasi berbasis android mendapat 19 keunggulan utama, sedangkan hasil pengembangan administrasi web mendapat 8 kelas baru pada framework berbasis situs. Pengujian unit selesai menggunakan strategi kotak putih dan pengujian persetujuan selesai menggunakan teknik penemuan. Efek samping dari pengujian unit dan pengujian persetujuan menghasilkan nilai 100%, yang berarti bahwa semua sorotan berfungsi sesuai dengan persyaratan yang ditentukan.

PROGRAM APLIKASI PEMBELAJARAN PEMROGRAMAN JAVA YANG ATRAKTIF BERBASIS ANDROID PADA SISTEM INFORMASI MANAJEMEN

Di Fakultas Ilmu Komputer (FILKOM) Universitas Brawijaya, hasil review menunjukkan bahwa 76% dari 100 mahasiswa FILKOM lebih tertarik pada materi pembelajaran selain mata kuliah pemrograman esensial. Keterbatasan sumber materi yang diperoleh dan pemanfaatan teknik Student Centered Learning di FILKOM dinilai kurang mengakomodir mahasiswa untuk memahami materi pembelajaran. Dengan cara ini, kerangka pembelajaran pemrograman java elektronik yang memikat telah dibuat dengan memanfaatkan teknik gamifikasi. Bagaimanapun, penelitian dari Baidu Study mengungkapkan bahwa klien aplikasi serbaguna 97% lebih besar dari program yang hanya 76%. Beberapa penelitian terkait gamification juga mengungkapkan bahwa judul eksplorasi tambahan adalah sejauh portabilitas. Mengingat informasi ini, penting untuk mengembangkan aplikasi pembelajaran pemrograman Java dalam bentuk serbaguna yang berjalan sebagai pelanggan, sehingga kerangka kerja saat ini dapat berfungsi sebagai server. Dalam pengujian ini, aplikasi berbasis pada tahap android lokal. Untuk bertukar informasi dengan server, penting untuk membuat administrasi web yang digunakan sebagai Application Programming Interface (API). Hasil pengembangan aplikasi berbasis android mendapat 19 keunggulan utama, sedangkan hasil pengembangan administrasi web mendapat 8 kelas baru pada framework berbasis situs. Pengujian unit selesai menggunakan strategi kotak putih dan pengujian persetujuan selesai menggunakan teknik penemuan. Efek samping dari pengujian unit dan pengujian persetujuan menghasilkan nilai 100%, yang berarti bahwa semua sorotan berfungsi sesuai dengan persyaratan yang ditentukan.

#ColonCancer: Social Media Discussions About Colorectal Cancer During the COVID-19 Pandemic

PURPOSE Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide. Social media platforms such as Twitter are extensively used to communicate about cancer care, yet little is known about the role of these online platforms in promoting early detection or sharing the lived experiences of patients with CRC. This study tracked Twitter discussions about CRC and characterized participating users to better understand public communication and perceptions of CRC during the COVID-19 pandemic. METHODS Tweets containing references to CRC were collected from January 2020 to April 2021 using Twitter's Application Programming Interface. Account metadata was used to predict user demographic information and classify users as either organizations, individuals, clinicians, or influencers. We compared the number of impressions across users and analyzed the content of tweets using natural language processing models to identify prominent topics of discussion. RESULTS There were 72,229 unique CRC-related tweets by 31,170 users. Most users were male (66%) and older than 40 years (57%). Individuals accounted for most users (44%); organizations (35%); clinicians (19%); and influencers (2%). Influencers made the most median impressions (35,853). Organizations made the most overall impressions (1,067,189,613). Tweets contained the following topics: bereavement (20%), appeals for early detection (20%), research (17%), National Colorectal Cancer Awareness Month (15%), screening access (14%), and risk factors (14%). CONCLUSION Discussions about CRC largely focused on bereavement and early detection. Online coverage of National Colorectal Cancer Awareness Month and personal experiences with CRC effectively stimulated goal-oriented tweets about early detection. Our findings suggest that although Twitter is commonly used for communicating about CRC, partnering with influencers may be an effective strategy for improving communication of future public health recommendations related to CRC.

Pengembangan Sistem Informasi Registrasi Mahasiswa Baru dengan Metode Analisis Gugus Kendali Mutu

Pendidikan sebagai industri produk dan jasa berbasis ilmu pengetahuan dan keterampilan menghadapi persaingan yang semakin kompetitif dengan banyaknya institusi baik dalam dan luar negeri yang operasional di Indonesia. Untuk meningkatkan daya saing, maka utilisasi teknologi informasi khususnya di era revolusi industri 4.0 menjadi kunci penting. Penelitian ini bertujuan untuk mengembangkan Sistem Informasi Registrasi Mahasiswa Baru (SIRMB) menggunakan kerangka open-source web-based application serta integrasinya dengan teknologi Application Programming Interface (API) Bank BNI menjadikan layanan administrasi yang terotomasi. Proses identifikasi masalah sampai perancangan solusi SIRMB menggunakan analisis gugus kendali mutu (QCC) dengan pendekatan metode Plan-Do-Check-Action (PDCA) sehingga menjamin perbaikan yang berkesinambungan. Penelitian ini berkontribusi terhadap perbaikan 76.9% terhadap proses kerja dengan eliminasi proses kerja manual registrasi mahasiswa baru, sehingga memberikan peningkatan kualitas layanan dan peningkatan produktivitas secara keseluruhan.

A Novel Mobile and IOT Enabled Application for Smart Energy Meter

Smart Energy Meters have significantly helped in easy reporting of energy consumption and the measurement of the same, since their introduction. They have replaced mainstream method of the house to house energy consumption data recording, but they are still reading with a lot of data inconsistencies between participating parties (energy suppliers and consumers). The purpose of this research is to develop a mobile web application with Internet of Things (IOT) and short message service (SMS) for consistent, transparent recording, monitoring of energy consumed, amount billed, infrastructure theft and meter control. Arduino, sensors and relay modules are some of the hardware components used with communication application programming interface (API) accessed through the Wi-Fi module. The communication between the hardware and the server is the response based on different commands, which includes turning on and off, setting threshold, requesting consumption and even paid for consumed power. The app will enable the consumer monitor their current energy consumption through the web and android interface and remotely turn the meter on and off. Stored data can be retrieved at any time. Keywords— Arduino, Billing, IOT, Power Consumption, Smart Electricity meter, SMS, Web Application

Serverless Geospatial Data Processing Workflow System Design

Geospatial data and related technologies have become an increasingly important aspect of data analysis processes, with their prominent role in most of them. Serverless paradigm have become the most popular and frequently used technology within cloud computing. This paper reviews the serverless paradigm and examines how it could be leveraged for geospatial data processes by using open standards in the geospatial community. We propose a system design and architecture to handle complex geospatial data processing jobs with minimum human intervention and resource consumption using serverless technologies. In order to define and execute workflows in the system, we also propose new models for both workflow and task definitions models. Moreover, the proposed system has new Open Geospatial Consortium (OGC) Application Programming Interface (API) Processes specification-based web services to provide interoperability with other geospatial applications with the anticipation that it will be more commonly used in the future. We implemented the proposed system on one of the public cloud providers as a proof of concept and evaluated it with sample geospatial workflows and cloud architecture best practices.