A Complete Environmental Intelligence System for LiDAR-Based Vegetation Management in Power-Line Corridors

This paper presents the first complete approach to achieving environmental intelligence support in the management of vegetation within electrical power transmission corridors. Contrary to the related studies that focused on the mapping of power lines, together with encroaching vegetation risk assessment, we realised predictive analytics with vegetation growth simulation. This was achieved by following the JDL/DFIG data fusion model for complementary feature extraction from Light Detection and Ranging (LiDAR) derived data products and auxiliary thematic maps that feed an ensemble regression model. The results indicate that improved vegetation growth prediction accuracy is obtained by segmenting training samples according to their contextual similarities that relate to their ecological niches. Furthermore, efficient situation assessment was then performed using a rasterised parametrically defined funnel-shaped volumetric filter. In this way, RMSE≈ 1 m was measured when considering tree growth simulation, while a 0.37 m error was estimated in encroaching vegetation detection, demonstrating significant improvements over the field observations.

Student Information Chatbot System

Conversational agents, also known as chatbots, are automated systems for engaging in two-way dialogue with human users. Nowadays the use of Chatbots is very popular in a large scale of applications especially in systems that provide an intelligence support to the user. In fact, to speed up the assistance, in many cases, these systems are equipped with Chatbots that can interpret the user questions and provide the right answers, in a fast and correct way. Chatbots typically provide a text-based user interface, allowing the user to type commands and receive text as well as text to speech response. When chat bot technology is integrated with popular web services it can be utilized securely by an even larger audience. The student information chat bot will analyse user’s queries and understand user’s message for appropriate response generation. This System will be a web application which provides answer to the query of the student very effectively. Students just have to put their query to the bot which is used for chatting. The system will use the algorithms to give appropriate answers to the user. If the answer is found invalid, then there is an option to report to admin so that the users query will be satisfied. These invalid questions can be deleted or modified by the admin of the system and an appropriate answer can be embedded in the database. The student will not have to go to the college for enquiring something. Student can use the chat bot to get the answers to their queries. Students can use this web based system for making enquiries at any point of time. This system may help students to stay updated with the college activities.

Classification of Diseases of The Urinary System using an Expert System

Purpose – Develop and use an Expert System (ES) to classify diseases of the urinary system. Design/methodology/approach – Computational experiments were divided into three phases, as described: Phase A: Database selection: We searched for a database that contains information on diseases of the urinary system. Phase B: Development and Implementation of the Expert System: Rules and variables were planned for the correct data manipulation, and the Expert System was created by implementing the rules and variables. Phase C: Validation of the Expert System: Expert System validated by specialists. Findings – The Expert System was validated by a general practitioner and, as such, was successful while carrying out the tests and results. In conclusion, the Expert System was generated to classify two diseases (Cystitis and Nephritis) of the urinary system. This was validated by a general practitioner who confirmed the accuracy of the information within the system developed and aimed of assisting the field of medicine for a specific organ. Originality/value – The development of the present work has made it possible to assist the specific diagnosis of two diseases of the urinary system. With the assistance of the Specialist System, professionals can be more confident when diagnosing diseases of the urinary system in patients. Keywords - Urinary System; Expert Systems; Artificial Intelligence; Support to The Diagnosis.

Peculiarities of interaction of an investigator and operations officers during the detection and investigation of fraud-related crimes connected with subsidy payments in the sphere of small and medium entrepreneurship

Sustainable socio-economic development of Russia is a strategic guideline for the creation of favorable conditions for entrepreneurship in the country. Article 6 of the Federal Law “On the development of small and medium entrepreneurship in Russia” of July 24, 2007 No 209 states that the governmental policy in this sphere is a part of the state socio-economic policy, and is a composition of political, economic, social, informational, legal, organizational, educational and other steps taken by Russia’s public and local authorities.  At the same time, in the last few years, the cases of illegal acquisition of budgetary funds by business entities in the form of federal, regional and local subsidies have been registered more and more often. Law enforcement agencies failed to effectively detect and investigate these crimes, which can be explained by the lack of methodological support of their work and modern tools based on information technologies. Intelligence support plays a significant role in the investigation of fraud connected with subsidies in the sphere of small and medium entrepreneurship. It is explained not only by the large amount of documentation and the spatiotemporal dissemination of a crime scene, but also by the fact that in most cases, the illegal acquisition of subsidies by small and medium business entities is pretends to be a legal economic activity.  The research subject is the laws of organizational and methodological support of the work of law-enforcement agencies aimed at the detection and investigation of fraud-related crimes. The scientific novelty of the research is determined by the solution of its tasks, and consists in the substantiation of conclusions about the natural interrelation between the organization and the method of investigation of fraud-related crimes connected with the acquisition of subsidies in the sphere of small and medium business, and the development of ways of their improvement.