A cloud computing platform of Internet-complex IACPaaS for development, management and use of multi-agent Internet services

The IACPaaS cloud platform (https://iacpaas.dvo.ru/) supports three models of providing cloud services - PaaS, SaaS and DaaS (Desktop as a Service) and is designed for development (including collective), management, and remote use :
- applied intelligent services - systems with knowledge bases for various classes of tasks and subject areas (expert systems, decision support systems, computer simulators, intelligent assistants, etc.);
- tools for creating, maintaining and ensuring the viability of applied services and their components (knowledge bases, databases, ontologies, etc.).
The toolkit takes into account the specifics of systems with knowledge bases (in particular, it is aimed at specialists of various types - experts, knowledge engineers, software developers), simplifies and automates their development, reduces maintenance work, thus ensuring their increased viability.
Key features and benefits of the platform:
• a single declarative semantic (conceptual) representation of all information (ontologies, knowledge bases, databases) and software components of applied and instrumental services, a single language for describing models (ontologies) of all components;
• explicit separation of component models from the components themselves for their reuse and a single two-level approach to the formation of all information and software components of services (first, a structural declarative model is formed, then the necessary component is created on it);
• an intuitive editor for the formation and modification of models of all components with automatic generation of editors of these components that support several types of user interfaces;
• mechanisms for linking various ontologies, knowledge bases, databases and their fragments;
• the ability to export / import information components and their models in JSON format;
• support of three technologies for developing intelligent services:
• basic (universal) technology;
• technology for developing intelligent services with interactive virtual environments;
• technologies for developing services with agents attached to the process of problem solving.

The platform is actively operated, work is underway to improve it and increase service functions. To date, the platform has created knowledge portals for the following subject areas:
•  medicine,
•  laser-based additive manufacturing,
•  verification of intuitive mathematical evidence,
•  autonomous uninhabited underwater vehicles,
•  knowledge on experimental diagnosis of crops,
•  data protection,
•  pedagogical psychology,
•  programming technology.
Today, the platform has more than 400 registered users both in Russia and abroad.
Unlike existing analogues, the platform has instrumental support for the development of all components of intelligent services. This toolkit is extensible. Unified principles, mechanisms and technologies for creating applied and instrumental services, unified tools for expanding and developing tools allow us to increase its functionality not only for developers, but also for users.
The core of the platform is implemented in the form of a combination of three processors - an information resource processor, an application processor and a user interface processor - each of which is a set of functions to support the corresponding components of application and tool services.
Received Certificates of the Federal Service for Intellectual Property on state registration of computer programs: No. 2012618347; No. 20133619809; No. 2013660086.

 

Cloud infrastructure for creating intelligent decision support systems for the diagnosis of arbitrary diseases

The cloud infrastructure includes a set of software and information components on the IACPaaS platform (https://iacpaas.dvo.ru/), designed to create decision support systems for the diagnosis of arbitrary diseases for practical medicine as cloud services. The introduction of such systems into medical practice is aimed at reducing the number of mistakenly diagnosed diseases.
The infrastructure supports expert-oriented formation and maintenance of medical knowledge bases based on the ontology of medical diagnostics. All knowledge bases are formed in uniform domain terms to ensure their unambiguous interpretation by both software services and various expert communities. For this purpose, the Database of medical terms and observations used by the means of forming knowledge bases has been created.
Key features and benefits of the infrastructure:
• Diagnostic ontology does not depend on sections of medicine and provides the following features:
• the formation of symptom complexes of diseases taking into account the categories of users;
• the formation of alternative symptom complexes with different approaches to identifying reliable signs of the disease;
• clarification of diagnoses taking into account the etiology, pathogenesis, course, etc. for differential diagnosis of diseases and the choice of appropriate treatment methods;
• the ability to specify a measure of fuzziness of a sign in a certain period of dynamics; taking into account the values of characteristics and signs changed by the impact of events; taking into account different variants of the dynamics of the values of the characteristics;
• generation of explanations of diagnostic results with various levels of detail;
• implementation of three approaches to the diagnosis of diseases: criticism of hypotheses, hypotheses, hypotheses with additional information;
• An environment for the continuous development of knowledge bases.

Infrastructure is actively operated, work is underway to improve it and increase service functions. To date, knowledge bases for the diagnosis of diseases from various branches of medicine have been created:
• a group of diseases of the gallbladder, biliary tract and pancreas;
• metabolic disorders of glucosaminoglycans;
• hemorrhagic fevers;
• respiratory diseases;
• diseases of the organs of vision. 

A fragment of the ontology of medical diagnostics

Unlike existing analogues, the infrastructure has an expert-oriented cloud-based development and continuous development environment for knowledge bases with interface support of various types. The ontology underlying the knowledge of diagnostics corresponds to the real ideas of medicine for a wide range of diseases and allows us to formalize any disease as a multifaceted and multivariate developing internal process.

 Environment for Continuous Knowledge Base Development

Received Certificate of the Federal Service for Intellectual Property on state registration of the database “Base of medical terminology and observations” No. 2019621179.

 

Cloud infrastructure for creating intelligent decision support systems for the search for drug treatment for diseases of any orientation

The cloud infrastructure includes a set of software and information components on the IACPaaS platform (https://iacpaas.dvo.ru/), designed to create decision support systems for the medical treatment of diseases of any orientation, based on both modern medical knowledge and current recommendations with taking into account personal indicators of the patient’s health, as well as the formation of a pharmacological guide.
The introduction of such systems into medical practice will prevent or significantly reduce the number of episodes of drug damage to the patient, including drug inefficiency, side effects of drugs, overdose, insufficient dosage, drug interactions.
The infrastructure supports expert-oriented formation and maintenance of medical knowledge bases based on the developed ontologies - the ontology of the pharmacological guide and the ontology of treatment of diseases.
All knowledge bases are formed in uniform domain terms to ensure their unambiguous interpretation by both software services and various expert communities.
Key features and benefits of the infrastructure:
• ontology of the pharmacological handbook and ontology of treatment of diseases do not depend on the sections of medicine and provide the following features:
• the formation of various models of therapy;
• the formation of alternative complexes according to the specific features of therapy, taking into account the various goals of therapy;
• formalization of descriptions of treatment regimens with a clear indication of the form of release and rules for taking the drug;
• the formation of descriptions of medicines in accordance with modern concepts of their effectiveness and safety of use;
• generation of explanations of the results of recommended treatment regimens with various levels of detail;
• An environment for the continuous development of knowledge bases.

Infrastructure is actively operated, work is underway to improve it and increase service functions. To date, knowledge bases on the treatment of diseases have been created:
• pathology of the gastrointestinal tract;
• infectious diseases.
Active work is underway to create new bases for drug treatment.

Fragment of the ontology of the pharmacological guide

 

               Fragment of the treatment ontology

Unlike existing analogues, the infrastructure has an expert-oriented cloud-based development and continuous development environment for knowledge bases with interface support of various types. Underlying the knowledge of treatment, the ontology corresponds to the real ideas of medicine for a wide range of diseases and allows you to formalize any protocol for the treatment of diseases.

 

Cloud service for modeling of inter-territorial transport communications

The service implements hybrid calculations in a heterogeneous environment and is intended for interactive modeling of inter-territorial trade cargo flows with the determination of the most probable values for communication systems in the presence of incomplete information.
The mathematical model of the problem belongs to the class of convex mathematical programming problems, involves the numerical solution of a nonlinear optimization problem with linear constraints, and is implemented on a high-performance computational server platform. Interactive control of communication parameters, interpretation and visualization of simulation results in the form of a graph are implemented on the IACPaaS cloud platform (https://iacpaas.dvo.ru/) with the usage of artificial intelligence methods.

 

Interactive editing of the graph involves changing the parameters of both the vertices of the graph and its arcs. When you select the appropriate graph element, the user receives structured and modifiable information about the object.

 

Using the obtained graph, the user can add a real map in order to evaluate the results of visualization more accurately.

 

Extensible knowledge portal on technological processes of laser-based additive  manufacturing of metal parts

The knowledge portal for :