Android-based Disease Identification on Crystal Guava's Leaf using Enterprise Unified Process Method

Subang Crystal Guava farmer groups have problems in the management and maintenance of plants that are still carried out by way of going down outside the Operating System Procedure (SOP) provided by the Subang Agriculture Service, especially in the management of disease prevention or plant pests and harvesting of Crystal Guava fruit . This makes the process of checking yields take a long time if it has to be adjusted to the SOP provisions. One alternative solution that aims to provide direction and treatment to farmers in managing guava crystals is to apply informatics technology in the form of an application model built for disease identification on Android-based guava leaves. This application uses the camera facilities on mobile phones to take photos of guava leaf samples. The research method used is a software development method (Enterprise Unified Process) whose stages include Construction, Transition, and Production. Java as a programming language, and Android Studio Tools as the editor. Application Identification of diseases on the guava leaves that were built after the trial can be used by the Crystal Guava Farmers in the Subang farmer group as a tool to determine the disease in the guava plants so that a method is obtained to treat the guava plants with a yield that is harvested expected to be optimal.

The $100 million question: Do we need to apply informatics to crystallization?

The PDB is currently growing at a rate of about 9000 structures annually, and 90% of these have been determined by X-ray diffraction methods. Each structure is the result of one or more crystals. Not every protein crystallises nor do all crystals diffract well enough; it has been estimated that of every 10 proteins that are purified, four will show some sign of crystallisation and one will crystallise robustly enough to obtain a structure1. Using these numbers, and making some educated guesses (for example, that most proteins are tested in 1000 crystallisation trials1) these 8000 structures represent 80,000 purified proteins, and 80,000,000 crystallisation trials which are set up each year. The cost of consumables, chemicals and direct labour to set up those trials varies, but can be estimated to be $0.1- $1, excluding the cost of the protein sample and any automation, suggesting that the structural biology community spends between 10 and 100 million each year on crystallisation. Any tools or insight that we can get from data mining or taking a computational approach to rationalize this process may not only profoundly change structural biology, but will make it much less expensive as well. We will discuss approaches to data mining, data standards, and software tools to enable a more rational approach to the process of crystallogenesis.

Programmatic Role of Education Libraries in Informatics to Support Preservice Teacher Preparation Programs

Background/Context The management, processing, and transformation of information constitute central tasks in education. Education informatics intersects the theories and practices of both informatics and education. In particular, informatics aids in the systematic incorporation of technology as educational stakeholders represent, process, and communicate information effectively. The systematic study of those informational structures and interactions, particularly the application of technology to discovering and communicating education information—education informatics—is less prevalent. Purpose/Objective/Research Question/Focus of Study As education librarians seek to collaborate with preservice teacher preparation programs, they need to apply informatics principles to optimize the library's ultimate impact on student achievement. Specifically, education librarians need to examine several levels of information processing systems: student, faculty, program, institution, and government entities. Furthermore, education librarians need to identify the conditions or environments of these information systems because the infrastructure, available resources, and knowledge base all impact student learning. Setting The settings for this study were preservice teacher preparation programs and academic libraries. Population/Participants/Subjects The participants were preservice teachers, teacher preparation faculty, and librarians. Research Design This is a secondary analytic essay. Conclusions/Recommendations With the burden that teacher preparation faculty have in offering a well-rounded and time-efficient program, postsecondary education libraries and their staff can support efforts to address informatics, leveraging their contributions of resources and informatics expertise. Academic librarians have in-depth training in informatics in that they look at information systematically. Particularly in those institutions where librarians are assigned subjects in which to specialize, they can link their professional skill to content-area needs.