The main goal of coal quality control in lignite mines is to supply coal to power plants within certain quality constraints. Coal properties can affect the efficiency, reliability, and availability of both the boiler and the emission control units. This paper presents a new based integrated mine process simulation approach to investigate the variability of the calorific value in exploitation a complex lignite deposits. Results provide valuable insight into the performance of a continuous mining system in terms of controlling coal quality variability.

Purpose: This paper aims to develop a system, which would enable efficient management and exploitation of documentation in electronic form, related to mining projects, with information retrieval and information extraction (IE) features, using various language resources and natural language processing. Design/methodology/approach: The system is designed to integrate textual, lexical, semantic and terminological resources, enabling advanced document search and extraction of information. These resources are integrated with a set of Web services and applications, for different user profiles and use-cases. Findings: The use of the system is illustrated by examples demonstrating keyword search supported by Web query expansion services, search based on regular expressions, corpus search based on local grammars, followed by extraction of information based on this search and finally, search with lexical masks using domain and semantic markers. Originality/value: The presented system is the first software solution for implementation of human language technology in management of documentation from the mining engineering domain, but it is also applicable to other engineering and non-engineering domains. The system is independent of the type of alphabet (Cyrillic and Latin), which makes it applicable to other languages of the Balkan region related to Serbian, and its support for morphological dictionaries can be applied in most morphologically complex languages, such as Slavic languages. Significant search improvements and the efficiency of IE are based on semantic networks and terminology dictionaries, with the support of local grammars.

Рад представља поступак дигитализације, структурног обогаћивања и изградње графа знања заснованог на историјској српској енциклопедији „Свезнање“ из 1937. године. Процес је обухватио скенирање, оптичко препознавање текста, ручну корекцију грешака, структурно уређивање и конверзију у формат TEI-XML. Посебна пажња посвећена је очувању изворног правописа и структуре текста, као и дефинисању прецизних упутстава за сараднике који су учествовали у корекцији и анотацији материјала. У раду су описани најчешћи проблеми дигитализације, укључујући мешање ћирилице и латинице, погрешно препознавање карактера и структурне грешке у тексту. Након корекције текста примењене су методе препознавања именованих ентитета (NER), повезивања ентитета са базом знања Википодаци (NEL), као и екстракције релација између ентитета. Енциклопедијски чланци су додатно класификовани према домену и семантичком типу, чиме је омогућена изградња семантички обогаћеног графа знања. Добијени ресурс представља значајан допринос дигиталној хуманистици и развоју језичких технологија за српски језик, омогућавајући напредну семантичку претрагу, анализу културног наслеђа и интеграцију са екосистемом повезаних отворених података. Додатно, применом великих језичких модела над препричаним и сажетим верзијама одредница генерисан је и скуп парова питања и одговора заснован на садржају енциклопедије, намењен даљим применама у системима за одговарање на питања и приступима заснованим на генерисању потпомогнутом претрагом (RAG).

The research presented in this paper aims at creating a bilingual (sr-en), easily searchable, hypertext, born-digital, corpus-based terminological database of raw material terminology for dictionary production. The approach is based on linking dictionaries related to the raw material domain, both digitally born and printed, into a lexicon structure, aligning terminology from different dictionaries as much as possible. This paper presents the main features of this approach, data used for compilation of the terminological database, the procedure by which it has been generated and a mobile application for its use. Available (terminological) resources will be presented—paper dictionaries and digital resources related to the raw material domain, as well as general lexica morphological dictionaries. Resource preparation started with dictionary (retro)digitisation and corpora enlargement, followed by adding new Serbian terms to general lexica dictionaries, as well as adding bilingual terms. Dictionary development is relying on corpus analysis, details of which are also presented. Usage examples, collocations and concordances play an important role in raw material terminology, and have also been included in this research. Some important related issues discussed are collocation extraction methods, the use of domain labels, lexical and semantic relations, definitions and subentries.

This paper will introduce Omeka, a platform for presentation of digital collections and a system for the management of their content. We will illustrate its application in the field of technical sciences (more specifically, in the field of mining) on the example of the digital library ROmeka@RGF. We have decided to use Omeka because it is simple, because it possesses comprehensive supporting documentation and because it does not require any attainment in information sciences, which makes it accessible for most users, and especially for mining engineers, to whom this digital library is chiefly intended. Documents assembled and stored in this digital library will serve as a basis for future research, extraction of terminology, tagging, extraction of knowledge etc.