An overview of decision table literature.

The present report contains an overview of the literature on decision tables since its origin. The goal is to analyze the dissemination of decision tables in different areas of knowledge, countries and languages, especially showing these that present the most interest on decision table use. In the first part a description of the scope of the overview is given. Next, the classification results by topic are explained. An abstract and some keywords are included for each reference, normally provided by the authors. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. Other examined topics are the theoretical or practical feature of each document, as well as its origin country and language. Finally, the main body of the paper consists of the ordered list of publications with abstract, classification and comments.

Concepts and Methods from Artificial Intelligence in Modern Information Systems – Contributions to Data-driven Decision-making and Business Processes

Today, organizations are facing a variety of challenging, technology-driven developments, three of the most notable ones being the surge in uncertain data, the emergence of unstructured data and a complex, dynamically changing environment. These developments require organizations to transform in order to stay competitive. Artificial Intelligence with its fields decision-making under uncertainty, natural language processing and planning offers valuable concepts and methods to address the developments. The dissertation at hand utilizes and furthers these contributions in three focal points to address research gaps in existing literature and to provide concrete concepts and methods for the support of organizations in the transformation and improvement of data-driven decision-making, business processes and business process management. In particular, the focal points are the assessment of data quality, the analysis of textual data and the automated planning of process models. In regard to data quality assessment, probability-based approaches for measuring consistency and identifying duplicates as well as requirements for data quality metrics are suggested. With respect to analysis of textual data, the dissertation proposes a topic modeling procedure to gain knowledge from CVs as well as a model based on sentiment analysis to explain ratings from customer reviews. Regarding automated planning of process models, concepts and algorithms for an automated construction of parallelizations in process models, an automated adaptation of process models and an automated construction of multi-actor process models are provided

Business Intelligence Tools for Supporting Modern Corporations

Tato práce se zabývá významem businessové inteligence v moderních podnicích. Nejprve budou popsány konkrétní technologie a nástroje patřící do businessové inteligence. Prezentován bude i jejich význam pro celkovou image a jeho pomoc pro lepší komunikaci mezi jednotlivými odděleními společnosti. Pro vyhodnocení bude vytvořena anketa, která bude zaměřena na lidi, kteří mají něco společného s moderními podniky a bude jim položena otázka, jak dalece rozumí nástrojům businessové inteligence a jejich významu pro moderní podniky samotné. Na základě tohoto průzkumu lze zjistit mezeru ve znalostech v moderních podnicích a do jaké míry ovlivňuje firmy a jejich funkčnost. Na konec budou na základě analýzy průzkumu předloženy možná řešení, silné a slabé stránky.The present thesis deals with the importance of business intelligence in modern enterprises. At first specific technologies and tools in Business Intelligence will be described. Presented will also be their importance for the overall image and its help for better communication among each department of the company. For the evaluation, a survey will be created which will be aimed at people who have something in common with modern enterprises and they will be asked how far they understand Business Intelligence tools and their importance for the modern enterprises themselves. Based on this survey might be found a gap of knowledge in modern enterprises and how far it affects the enterprises and their functionality. Possible solutions, strengths and limitations based on the analysis of the survey will come up in the end.

Доповнена реальність в освіті

This volume represents the proceedings of the 1st International Workshop on Augmented Reality in Education (AREdu 2018), held in Kryvyi Rih, Ukraine, in October 2, 2018. It comprises 24 contributed papers that were carefully peer-reviewed and selected from 41 submissions. The accepted papers present the state-of-the-art overview of successful cases and provides guidelines for future research.Цей том репрезентує матеріали 1-го Міжнародного семінару "Доповнена реальність в освіті" (AREdu 2018), що відбувя 2 жовтня 2018 року в м. Кривий Ріг, Україна. До нього входять 24 статті, які були ретельно переглянуті та обрані з 41 подання. У прийнятих роботах представлений найсучасніший огляд успішних випадків та окреслено напрями майбутніх досліджень

The application of process mining to care pathway analysis in the NHS

Background: Prostate cancer is the most common cancer in men in the UK and the sixth-fastest increasing cancer in males. Within England survival rates are improving, however, these are comparatively poorer than other countries. Currently, information available on outcomes of care is scant and there is an urgent need for techniques to improve healthcare systems and processes. Aims: To provide prostate cancer pathway analysis, by applying concepts of process mining and visualisation and comparing the performance metrics against the standard pathway laid out by national guidelines. Methods: A systematic review was conducted to see how process mining has been used in healthcare. Appropriate datasets for prostate cancer were identified within Imperial College Healthcare NHS Trust London. A process model was constructed by linking and transforming cohort data from six distinct database sources. The cohort dataset was filtered to include patients who had a PSA from 2010-2015, and validated by comparing the medical patient records against a Case-note audit. Process mining techniques were applied to the data to analyse performance and conformance of the prostate cancer pathway metrics to national guideline metrics. These techniques were evaluated with stakeholders to ascertain its impact on user experience. Results: Case note audit revealed 90% match against patients found in medical records. Application of process mining techniques showed massive heterogeneity as compared to the homogenous path laid out by national guidelines. This also gave insight into bottlenecks and deviations in the pathway. Evaluation with stakeholders showed that the visualisation and technology was well accepted, high quality and recommended to be used in healthcare decision making. Conclusion: Process mining is a promising technique used to give insight into complex and flexible healthcare processes. It can map the patient journey at a local level and audit it against explicit standards of good clinical practice, which will enable us to intervene at the individual and system level to improve care.Open Acces

Measurable Safety of Automated Driving Functions in Commercial Motor Vehicles

With the further development of automated driving, the functional performance increases resulting in the need for new and comprehensive testing concepts. This doctoral work aims to enable the transition from quantitative mileage to qualitative test coverage by aggregating the results of both knowledge-based and data-driven test platforms. The validity of the test domain can be extended cost-effectively throughout the software development process to achieve meaningful test termination criteria

Proceedings of the Conference on Production Systems and Logistics: CPSL 2022

[no abstract available

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202