Knowledge-based control of an adaptive interface

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations

Evaluation of database technologies for the CTBT Knowledge Base prototype

This document examines a number of different software technologies in the rapidly changing field of database management systems, evaluates these systems in light of the expected needs of the Comprehensive Test Ban Treaty (CTBT) Knowledge Base, and makes some recommendations for the initial prototypes of the Knowledge Base. The Knowledge Base requirements are examined and then used as criteria for evaluation of the database management options. A mock-up of the data expected in the Knowledge Base is used as a basis for examining how four different database technologies deal with the problems of storing and retrieving the data. Based on these requirement and the results of the evaluation, the recommendation is that the Illustra database be considered for the initial prototype of the Knowledge Base. Illustra offers a unique blend of performance, flexibility, and features that will aid in the implementation of the prototype. At the same time, Illustra provides a high level of compatibility with the hardware and software environments present at the US NDC (National Data Center) and the PIDC (Prototype International Data Center)

Towards MKM in the Large: Modular Representation and Scalable Software Architecture

MKM has been defined as the quest for technologies to manage mathematical knowledge. MKM "in the small" is well-studied, so the real problem is to scale up to large, highly interconnected corpora: "MKM in the large". We contend that advances in two areas are needed to reach this goal. We need representation languages that support incremental processing of all primitive MKM operations, and we need software architectures and implementations that implement these operations scalably on large knowledge bases. We present instances of both in this paper: the MMT framework for modular theory-graphs that integrates meta-logical foundations, which forms the base of the next OMDoc version; and TNTBase, a versioned storage system for XML-based document formats. TNTBase becomes an MMT database by instantiating it with special MKM operations for MMT.Comment: To appear in The 9th International Conference on Mathematical Knowledge Management: MKM 201

analysis of a data flow in a financial iot system

Abstract Data retrieving, analysis e management are usually known as complex task in financial contexts. In an Internet of Things (IoT) system data-flow processes represent the knowledge base used in mathematical models for credits and financial products. Several sources such as distributed database systems, portals and local information are generally used as input of inferring models. In this paper we describe an overview of software tools, methodologies and strategies in real data-flow system

Intelligent Web Facility To Enhance Yield,Resilience And Sustainability Ukrainian And USA Farms

This paper proposes to implement a computational model and intelligent software for farms, that give the farmer a set of robust and viable options for crop, soil, and water management, enhance crop resiliency to climate change, the effects of pests, plant diseases and other environmental factors. Model and intelligent software for farms includes the following tasks: search, analysis and storage in a dedicated base of relevant data gleaned from the Internet, the interaction with the farmer through a dedicated interface, the development of the farmer’s solution by database and integrated knowledge base for plant protection

Marketing Risk Management of Palm Oil Based Biodiesel Agroindustry

Biodiesel is fuel generates from vegetable oils that have properties similar to diesel oil. The advantages of biodiesel compared to diesel is an environmentally friendly fuel because it produces much lower emissions (sulfur free, low smoke number) in accordance with global issues, higher cetane number (> 57) so that the combustion efficiency is better than diesel, lubrication properties of the piston engine; biodegradable, a renewable energy because it is made from natural materials, and improve the independence of fuel supply because it can be produced locally. The purpose of this research is to design the risk management decision support system for agro-industry development biodiesel of oil palm-based. Determination of objectives and risk management strategies using the used to obtain an alternative value in the aspect of marketing. This research resulted in a decision support system that is useful to help decision makers in addressing the risk of agro-bio-diesel. Risk management model is designed in a decision support system  (DSS), can be used by industrial users and investors in the field of biodiesel. DSS software development using Microsoft Visual Basic Version 6.0 consists of three main components namely database management system, knowledge base management system and model base management system. Model base management system consists of risk marketing analysis

A landslide data base model for ClirTheRoads project in Serbia

Within the project Mainstreaming Climate Resilience in the Road Transportation Management in Serbia (CliRtheRoads), a complex software solution was developed to support Public Enterprise Roads of Serbia in climate change adaptation planning and management. The software solution comprises 1) web portal for data entry and management for authorised users 2) publicly available web GIS part 3) mobile GIS application and 4) back-end database (Figure 1). In order to store and process the data collected during field visits and surveys, the data base developed in project first phase (Valjevo test area), was modified to include new datasets and to store new datatypes (as floods), and new modules (as activity cost) for Kraljevo test area. Both test areas have been chosen due theirs diversified characteristics, many climate related hazards, and the fact they suffered greatly from disasters recently (Abolmasov et al. 2017, Abolmasov et al. 2021). The database was upgraded to new model aimed for maintaining legacy data from both test areas, but also for future infrastructure resilience projects based on same approach, to enable that all data will be stored and mapped in a unified manner. The data model include 1) main concepts (entity types) for the instabilities, with detailed data comprising common and specific attributes, 2) storage of multimedia (mainly photo from field work, but possible video as well), 3) knowledge base with cost of activities, including catalogue per each entity type with job type and description, unit and total price, maintenance type (regular maintenance, rehabilitation, urgent maintenance), including recommending activities (system allow user to add specific activities, description and cost that is further calculated and aggregated with other data); 4) secondary data from other sources (other projects, legacy data and external resources), or from interpreted data. The data was stored in the PostgreSQL Database, a web application was developed (using PHP) to facilitate data input, maintain knowledge database and calculate cost of recommended activities. There is a total of 461 records with fully described instabilities (slides, falls, topples, flows), documented by large number of photographs from the field. Additionally, every record is supplemented by engineering solution to support field engineers or decision makers for better road management in climate changing conditions