scholarly journals Toward Process Variability Management in Online Examination Process in German Universities: A State of the Art

2021 ◽  
pp. 111-130
Author(s):  
Maryam Heidari ◽  
Oliver Arnold
Keyword(s):  
Business Process ◽  
State Of The Art ◽  
Modeling Processes ◽  
Process Variability ◽  
New Approach ◽  
Online Examination ◽  
Legal Restrictions ◽  
Variability Management ◽  
Examination Process ◽  
Multiple Variants

AbstractIn contemporary organizations, multiple variants of the same business process are often considerable. Such business process variability has caused considerable challenges, both while modeling processes and in their execution. In order to develop a new approach to managing process variants, or extend an existing one, in this research, we review the state of the art in a particular area: online examination processes. We show to what extent variability should be considered in exam processes, whether this is due to special legal restrictions and regulations, different exam frameworks, or even different technical infrastructure. This could be the foundation for developing an approach to managing process variability in the field of e-assessment. Initial findings indicate that examination processes have many similarities, but also considerable differentiation. Therefore, there an appropriate model needs to be developed in order to manage variability in e-assessment and the developed approach must then be validated in identifying faculties. This paper constitutes a first step in this direction.

Modeling Business Process Variability for Design-Time Configuration

2011 ◽  
pp. 204-228 ◽  
Author(s):  
Macello La Rosa ◽  
Marlon Dumas ◽  
Arthur H.M. ter Hofstede
Keyword(s):  
Business Process ◽  
Process Model ◽  
Process Models ◽  
Attractive Alternative ◽  
Process Variability ◽  
Design Time ◽  
Reference Process ◽  
Multiple Variants

A reference process model represents multiple variants of a common business process in an integrated and reusable manner. It is intended to be individualized in order to fit the requirements of a specific organization or project. This practice of individualizing reference process models provides an attractive alternative with respect to designing process models from scratch; in particular, it enables the reuse of proven practices. This chapter introduces techniques for representing variability in the context of reference process models, as well as techniques that facilitate the individualization of reference process models with respect to a given set of requirements.

scholarly journals Execution of Knowledge-Intensive Processes by Utilizing Ontology-Based Reasoning

2021 ◽  
Author(s):  
Eric Rietzke ◽  
Carsten Maletzki ◽  
Ralph Bergmann ◽  
Norbert Kuhn
Keyword(s):  
Business Process ◽  
Process Model ◽  
State Of The Art ◽  
Inference Mechanism ◽  
Ongoing Research ◽  
New Approach ◽  
The Subject ◽  
Knowledge Intensive ◽  
Process Elements ◽  
Bp Model

AbstractModeling and executing knowledge-intensive processes (KiPs) are challenging with state-of-the-art approaches, and the specific demands of KiPs are the subject of ongoing research. In this context, little attention has been paid to the ontology-driven combination of data-centric and semantic business process modeling, which finds additional motivation by enabling the division of labor between humans and artificial intelligence. Such approaches have characteristics that could allow support for KiPs based on the inferencing capabilities of reasoners. We confirm this as we show that reasoners can infer the executability of tasks based on a currently researched ontology- and data-driven business process model (ODD-BP model). Further support for KiPs by the proposed inference mechanism results from its ability to infer the relevance of tasks, depending on the extent to which their execution would contribute to process progress. Besides these contributions along with the execution perspective (start-to-end direction), we will also show how our approach can help to reach specific process goals by inferring the relevance of process elements regarding their support to achieve such goals (end-to-start direction). The elements with the most valuable process progress can be identified in the intersection of both, the execution and goal perspective. This paper will introduce this new approach and verifies its practicability with an evaluation of a KiP in the field of emergency call centers.

A new approach based on graph matching and evolutionary approach for sport scheduling problem

2020 ◽  
pp. 1-16
Author(s):  
Meriem Khelifa ◽  
Dalila Boughaci ◽  
Esma Aïmeur
Keyword(s):  
Graph Matching ◽  
State Of The Art ◽  
Travel Cost ◽  
Round Robin ◽  
New Approach ◽  
Traveling Tournament Problem ◽  
Significant Interest ◽  
National League ◽  
Better Than

The Traveling Tournament Problem (TTP) is concerned with finding a double round-robin tournament schedule that minimizes the total distances traveled by the teams. It has attracted significant interest recently since a favorable TTP schedule can result in significant savings for the league. This paper proposes an original evolutionary algorithm for TTP. We first propose a quick and effective constructive algorithm to construct a Double Round Robin Tournament (DRRT) schedule with low travel cost. We then describe an enhanced genetic algorithm with a new crossover operator to improve the travel cost of the generated schedules. A new heuristic for ordering efficiently the scheduled rounds is also proposed. The latter leads to significant enhancement in the quality of the schedules. The overall method is evaluated on publicly available standard benchmarks and compared with other techniques for TTP and UTTP (Unconstrained Traveling Tournament Problem). The computational experiment shows that the proposed approach could build very good solutions comparable to other state-of-the-art approaches or better than the current best solutions on UTTP. Further, our method provides new valuable solutions to some unsolved UTTP instances and outperforms prior methods for all US National League (NL) instances.

scholarly journals Bin2vec: learning representations of binary executable programs for security tasks

Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Shushan Arakelyan ◽  
Sima Arasteh ◽  
Christophe Hauser ◽  
Erik Kline ◽  
Aram Galstyan
Keyword(s):  
Program Analysis ◽  
State Of The Art ◽  
Classification Error ◽  
New Approach ◽  
Convolutional Networks ◽  
Computational Program ◽  
Functional Algorithm ◽  
Binary Program ◽  
Vulnerability Discovery ◽  
Executable Programs

AbstractTackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability to a number of downstream tasks. We introduce Bin2vec, a new approach leveraging Graph Convolutional Networks (GCN) along with computational program graphs in order to learn a high dimensional representation of binary executable programs. We demonstrate the versatility of this approach by using our representations to solve two semantically different binary analysis tasks – functional algorithm classification and vulnerability discovery. We compare the proposed approach to our own strong baseline as well as published results, and demonstrate improvement over state-of-the-art methods for both tasks. We evaluated Bin2vec on 49191 binaries for the functional algorithm classification task, and on 30 different CWE-IDs including at least 100 CVE entries each for the vulnerability discovery task. We set a new state-of-the-art result by reducing the classification error by 40% compared to the source-code based inst2vec approach, while working on binary code. For almost every vulnerability class in our dataset, our prediction accuracy is over 80% (and over 90% in multiple classes).

scholarly journals Target Localization via Integrated and Segregated Ranging Based on RSS and TOA Measurements

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 230 ◽  
Author(s):  
Slavisa Tomic ◽  
Marko Beko
Keyword(s):  
State Of The Art ◽  
Hybrid Approach ◽  
Critical Distance ◽  
Heuristic Approach ◽  
Target Localization ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Individual Measurement ◽  
New Approach ◽  
Non Line Of Sight

This work addresses the problem of target localization in adverse non-line-of-sight (NLOS) environments by using received signal strength (RSS) and time of arrival (TOA) measurements. It is inspired by a recently published work in which authors discuss about a critical distance below and above which employing combined RSS-TOA measurements is inferior to employing RSS-only and TOA-only measurements, respectively. Here, we revise state-of-the-art estimators for the considered target localization problem and study their performance against their counterparts that employ each individual measurement exclusively. It is shown that the hybrid approach is not the best one by default. Thus, we propose a simple heuristic approach to choose the best measurement for each link, and we show that it can enhance the performance of an estimator. The new approach implicitly relies on the concept of the critical distance, but does not assume certain link parameters as given. Our simulations corroborate with findings available in the literature for line-of-sight (LOS) to a certain extent, but they indicate that more work is required for NLOS environments. Moreover, they show that the heuristic approach works well, matching or even improving the performance of the best fixed choice in all considered scenarios.

Social business process management

2019 ◽  
Vol 26 (1) ◽  
pp. 191-211
Author(s):  
Patricia Bazan ◽  
Elsa Estevez
Keyword(s):  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
New Technologies ◽  
State Of The Art ◽  
Implicit Knowledge ◽  
Social Software ◽  
Social Business ◽  
Content Type

Purpose The purpose of this paper is to assess the state of the art of social business process management (Social BPM), explaining applied approaches, existing tools and challenges and to propose a research agenda for encouraging further development of the area. Design/methodology/approach The methodology comprises a qualitative analysis using secondary data. The approach relies on searches of scientific papers conducted in well-known databases, identifying research work related to Social BPM solutions and those contributing with social characteristics to BPM. Based on the identified papers, the authors selected the most relevant and the latest publications, and categorized their contributions and findings based on open and selective coding. In total, the analysis is based on 51 papers that were selected and analyzed in depth. Findings Main results show that there are several studies investigating modeling approaches for socializing process activities and for capturing implicit knowledge possessed and used by process actors, enabling to add some kind of flexibility to business processes. However, despite the proven interest in the area, there are not yet adequate tools providing effective solutions for Social BPM. Based on our findings, the authors propose a research agenda comprising three main lines: contributions of social software (SS) to Social BPM, Social BPM as a mechanism for adding flexibility to and for discovering new business processes and Social BPM for enhancing business processes with the use of new technologies. The authors also identify relevant problems for each line. Practical implications Some SS tools, like wikis, enable managing social aspects in executing business processes and can be used to coordinate simple business processes. Despite they are commonly used, they are not yet mature tools supporting Social BPM and more efficient tools are yet to appear. The lack of tools preclude organizations from benefitting from implicit knowledge owned by and shared among business process actors, which could contribute to better-informed decisions related to organizational processes. In addition, more research is needed for considering Social BPM as an approach for organizations to benefit from the adoption of new technologies in their business processes. Originality/value The paper assesses the state of the art in Social BPM, an incipient area in research and practice. The area can be defined as the intersection of two bigger areas highly relevant for organizations; on the one hand, the management and execution of business processes; and on the other hand, the use of social software, including social media tools, for leveraging on implicit knowledge shared by business process actors to improving efficiency of business processes.

scholarly journals TripletProt: Deep Representation Learning of Proteins based on Siamese Networks

2020 ◽  
Author(s):  
Esmaeil Nourani ◽  
Ehsaneddin Asgari ◽  
Alice C. McHardy ◽  
Mohammad R.K. Mofrad
Keyword(s):  
Functional Annotation ◽  
Cellular Localization ◽  
State Of The Art ◽  
Language Model ◽  
Representation Learning ◽  
Learning Problems ◽  
Ppi Network ◽  
New Approach ◽  
Protein Protein Interaction ◽  
Siamese Networks

AbstractWe introduce TripletProt, a new approach for protein representation learning based on the Siamese neural networks. We evaluate TripletProt comprehensively in protein functional annotation tasks including sub-cellular localization (14 categories) and gene ontology prediction (more than 2000 classes), which are both challenging multi-class multi-label classification machine learning problems. We compare the performance of TripletProt with the state-of-the-art approaches including recurrent language model-based approach (i.e., UniRep), as well as protein-protein interaction (PPI) network and sequence-based method (i.e., DeepGO). Our TripletProt showed an overall improvement of F1 score in the above mentioned comprehensive functional annotation tasks, solely relying on the PPI network. TripletProt and in general Siamese Network offer great potentials for the protein informatics tasks and can be widely applied to similar tasks.

scholarly journals Graph Algorithms for Word Sense Disambiguation in Biomedicine

2015 ◽  
Author(s):  
Rodrigo Goulart ◽  
Juliano De Carvalho ◽  
Vera De Lima
Keyword(s):  
Text Mining ◽  
Graph Algorithms ◽  
State Of The Art ◽  
Word Sense Disambiguation ◽  
The State ◽  
Word Sense ◽  
New Approach ◽  
Similar Performance ◽  
Sense Disambiguation ◽  
Different Levels

Word Sense Disambiguation (WSD) is an important task for Biomedicine text-mining. Supervised WSD methods have the best results but they are complex and their cost for testing is too high. This work presents an experiment on WSD using graph-based approaches (unsupervised methods). Three algorithms were tested and compared to the state of the art. Results indicate that similar performance could be reached with different levels of complexity, what may point to a new approach to this problem.

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