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Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The purpose of this paper is to illustrate that process mining can do with events what spreadsheets can do with numbers.

The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes.

Differences and commonalities between spreadsheets and process mining are described. Unlike process mining tools like ProM, spreadsheets programs cannot be used to discover processes, check compliance, analyze bottlenecks, animate event data, and provide operational process support. Pointers to existing process mining tools and their functionality are given.

Event logs and operational processes can be found everywhere and process mining techniques are not limited to specific application domains. Comparable to spreadsheet software widely used in finance, production, sales, education, and sports, process mining software can be used in a broad range of organizations.

The paper provides an original view on process mining by relating it to the spreadsheets. The value of spreadsheet-like technology tailored toward the analysis of behavior rather than numbers is illustrated by the over 20 commercial process mining tools available today and the growing adoption in a variety of application domains.

The lecture method has been compared with teaching methods such as flip learning, cooperative learning and simulations to establish which holds the key to students' understanding of concepts. What is bereft in the education literature is its comparative efficiency with the culturo-techno contextual approach (CTCA) in the teaching of computer science education.

This study adopted the quasi-experimental design to determine the efficacy of the CTCA in breaking difficulties related to the study of spreadsheets as a difficult concept in the Nigerian computer science education curriculum. Junior high school students studying computer science education participated in the study. The control group had 30 students, with 35 students in the experimental group. The experimental group was taught using CTCA, while the control group used the lecture method. The spread sheet achievement test, which had 40 items on spreadsheet, was used to collect data.

The results showed that the experimental group significantly outperformed the control group [F (1,60) = 41.89; p < 0.05]. The findings showed the potential of CTCA in improving students' performance in spreadsheets in the computer science education curriculum.

The originality of this study is hinged on its ground-breaking test of the CTCA to the study of the spreadsheet. The findings of this study indicate its efficacy in improving students' understanding of spreadsheet and computer science education.

Although Public Research Institutions (PRIs) are large technology producers, they lack automated information tools that follow technical and scientific criteria for assessing and valuing patents. The assessment and valuation processes are stages of technology transfer (TT) that make it possible to obtain productive arrangements and guide the efforts of those involved in the development, maintenance and negotiation. This study aims to analyze the hybrid model of assessment and valuation of technologies by Soares (2018), applying the ‘Valorativo' software. In addition to patent value and indicator scores, the methods allow an understanding of the technology portfolio and its management.

This research is quali-quantitative, following an approach of applied nature and descriptive objectives. The research has bibliographical, documental and case study features based on the software development methodologies described in the study and the theoretical framework.

The Valorativo software assisted in the analysis of ten patents on PRIs. With the data collection and patent analysis, PAT1 scored highest among engineering patents, PAT3 scored highest among pharmaceutical patents and PAT10 scored highest among biotechnology patents. Five of the assessed patents resulted in a surplus of net present value (NPV), final net present value (NPVF) and royalties; revenue expectations outpaced investments.

The authors based the developed software on Soares’s (2018) methodology, with additional calculations and graphs. The Web software and the spreadsheet with Visual Basic for Application (VBA) were developed to deal with the patents assessment and valuation, helping in the analysis of their Legal Value, Technological Value and Market Conditions in the assessment process, and the Discounted Cash Flow and NPV in the valuation process.

The software helps with patent analysis and can generate indicators for traders, technology holders and researchers. Thus, it was necessary to understand and develop a theoretical-applied framework to outline and replicate the methodology clearly and easily.

Despite South Africa’s ailing electrical grid, substantial renewable energy (RE) integration is planned for the country. As grid-integrated RE affects all grids differently, this study aims to develop an adaptable grid code-guided renewable power plant (RPP) control real-time simulation testbed, tailored to South African grid code requirements to study grid-integrated RE’s behaviour concerning South Africa’s unique conditions.

The testbed is designed using MATLAB’s Simulink and live script environments, to create an adaptable model where grid, RPP and RPP guiding grid codes are tailorable. This model is integrated with OPAL-RT’s RT-LAB and brought to real-time simulation using OPAL-RT’s OP4510 simulator. Voltage, frequency and short-circuit event case studies are performed through which the testbed’s abilities and performance are assessed.

Case study results show the following. The testbed accurately represents grid code voltage and frequency requirements. RPP point of connection (POC) conditions are consistently recognized and tracked, according to which the testbed then operates simulated RPPs, validating its design. Short-circuit event simulations show the simulated wind farm supports POC conditions relative to short-circuit intensity by curtailing active power in favour of reactive power, in line with local grid code requirements.

To the best of the authors’ knowledge, this is the first design of an adaptable grid code-guided RPP control testbed, tailored to South African grid code requirements in line with which RPP behavioural and grid integration studies can be performed.

The purpose of this paper is to develop an original model and a solution procedure for solving jointly three main strategic fleet management problems (fleet composition, replacement and make-or-buy), taking into account interdependencies between them.

The three main strategic fleet management problems were analyzed in detail to identify interdependencies between them, mathematically modeled in terms of integer nonlinear programing (INLP) and solved using evolutionary based method of a solver compatible with a spreadsheet.

There are no optimization methods combining the analyzed problems, but it is possible to mathematically model them jointly and solve together using a solver compatible with a spreadsheet obtaining a solution/fleet management strategy answering the questions: Keep currently exploited vehicles in a fleet or remove them? If keep, how often to replace them? If remove then when? How many perspective/new vehicles, of what types, brand new or used ones and when should be put into a fleet? The relatively large scale instance of problem (50 vehicles) was solved based on a real-life data. The obtained results occurred to be better/cheaper by 10% than the two reference solutions – random and do-nothing ones.

The methodology of developing optimal fleet management strategy by solving jointly three main strategic fleet management problems is proposed allowing for the reduction of the fleet exploitation costs by adjusting fleet size, types of exploited vehicles and their exploitation periods.

The purpose of this paper is to investigate the contribution of a project management approach to develop a tool to support the management of Brazilian stricto sensu graduate programs (SS-GP). The Adaptive approach was chosen by applying the Project Management Life Cycle (PMLC) method.

The study corresponds to the concept of applied research. The qualitative approach was used. The research strategy was the action research, where participants cooperate to understand their environment, identify problems and seek a solution, simultaneously producing and using the knowledge produced.

The results showed one possible way to apply a contingency project management approach to develop the tool. In addition, indicated that its application facilitated the project work, especially when finding a solution for the project’s development and when dealing with the changes inherent to the uncertainties about the problem.

The lack of more updated information and the limitation of time and resources led to the reduction of the environment scope and of the number of functionalities developed.

To contribute to the generation of knowledge and expertise to support the management of SS-GP in activities such as providing information to the CAPES evaluation system, academic production analysis, collaborative researcher network analysis and post-graduation program monitoring and evaluation.

To fill a gap pointed out by several studies, that it is not possible to automatically generate input lists to be processed by ScriptSucupira tool, based on filtered criteria, comprising the entire universe of the Brazilian SS-PG. The creators of ScriptSucupira also declared to ignore the existence of an artifact similar to that.

This study evaluates “potentials for using tourism in promoting indigenous resources for community development at Musina Municipality, Limpopo Province, South Africa.”

The study used a questionnaire survey, focus group discussions, and field observations to gather data. Microsoft Excel, Spreadsheet, cross-tabulation analysis, and manual sorting contributed to quantitative and qualitative data analyses.

The study uncovered vast significant indigenous species, resources, and tourism potentials with low impacts of indigenous species and resource benefits to the local communities. The details pointing to the actual and potential indigenous resources situations around tourism activities in Musina municipality emerged prominently. Thus, the study concluded such significant indigenous species, resources, and better tourism potentials need a well-combined strategy to channel the benefits to the local community's livelihoods.

The issue of indigenous resources, forests, trees, and tourism concerning rural community livelihoods has become of curiosity in the past few years. Nonetheless, few such studies have investigated the synergies between tourism and significant indigenous species and resources to improve their livelihoods.

This study assesses the “possibilities of utilizing sustainable tourism to improve community sustenance in Musina Municipality, Limpopo, South Africa.”

Therefore, to competently discern the implications of tourism in Musina Municipality, data got accumulated by questionnaire surveys, interviews, focus group discussions, document reviews and field observations. Thus, Microsoft Excel, Spreadsheet and Cross-Tabulation Analysis provided both quantitative and qualitative data analyses.

The study identified immense tourism potentials attached to low tourism influences and privileges on the local community's advancement. The relationships and contributory factors pointing to the present and latent tourism situations in Musina Municipality got critiqued. The study inferred that the Musina Municipality is well enriched with tourism potentials and necessitates a fitting tourism plan to profits the locals.

Musina Municipality is one of the driest districts in the remote North of Limpopo Province, South Africa. It is aggregated by meager livelihoods of rural communities, as do most rural communities abroad. However, the Municipality exemplifies some of the numerous tourism-based areas in the Vhembe District of Limpopo. The undertakings of tourism, community sustenance and sustainable promotion have been more proceeding to the lead. However, diverse investigations neglect to efficiently estimate the fundamental points and the complete functions of multiple forms of tourism in community development within many rural expanses.

User-generated social media comments can be a useful source of information for understanding online corporate reputation. However, the manual classification of these comments is challenging due to their high volume and unstructured nature. The purpose of this paper is to develop a classification framework and machine learning model to overcome these limitations.

The authors create a multi-dimensional classification framework for the online corporate reputation that includes six main dimensions synthesized from prior literature: quality, reliability, responsibility, successfulness, pleasantness and innovativeness. To evaluate the classification framework’s performance on real data, the authors retrieve 19,991 social media comments about two Finnish banks and use a convolutional neural network (CNN) to classify automatically the comments based on manually annotated training data.

After parameter optimization, the neural network achieves an accuracy between 52.7 and 65.2 percent on real-world data, which is reasonable given the high number of classes. The findings also indicate that prior work has not captured all the facets of online corporate reputation.

For practical purposes, the authors provide a comprehensive classification framework for online corporate reputation, which companies and organizations operating in various domains can use. Moreover, the authors demonstrate that using a limited amount of training data can yield a satisfactory multiclass classifier when using CNN.

This is the first attempt at automatically classifying online corporate reputation using an online-specific classification framework.