Hui Chen, Miguel Baptista Nunes

The purpose of the study reported in this paper was to identify how experience and tacit knowledge can be externalized and articulated in a way that they can be the object of electronic records management (ERM) as well as establish the areas of convergence between ERM and knowledge management (KM). The study employed an inductive qualitative approach based on a single case study of a successful software (SW) development private company that specializes in S W for archive management. 25 participants from this Chinese software company were selected based on their role in SW design and development and were interviewed using a semi-structured interview script. Gathered data were analysed by using an a priori thematic analysis approach, which was focused on the processes of externalisation for tacit knowledge into explicit knowledge that can be used by using ERM. The findings of this research suggest that evidence of experience is best defined by story -telling a nd unstructured narratives that capture tacit knowledge and are then easily managed through ERM. Knowledge which is derived from experience often affects and helps to improve the performance of agents in human activity systems of all types, ranging from b usiness org anizations to social networks. However, both tacit knowledge and evidence of experience are hard to capture, represent and maintain by organizations since they reside in individual’s minds rather than in information repositories. Therefore, more than theoretical research and propositions there is a need to devise clear processes to translate and externalize tacit knowledge into explicit one that can then be stored, shared and used. This study contributes to this practical and applied KM and ERM research and provides new and practice grounded insights in this area.

Joana Margarida Miguel, Maria João Varanda Pereira, Pedro Rangel Henriques, Mario Berón

The technology of nowadays allows to easily extract, store, process and use information about individuals and organizations. The increase of the amount of data collected and its value to our society was, at first, a great advance that could be used to optimize processes, find solutions and support decisions but also brought new problems related with lack of privacy and malicious attacks to confidential information. In this paper, a tool to anonymize datab ases is presented. It can be used by data publishers to protect information from attacks controlling the desired privacy level and the data usefulness. In order to specify these requirements a DSL ( PrivasL) is used and the automatization of repository tran sformation, that is based on language processing techniques, is the novelty of this work.

AND DATA ANALYTICS FOR UNIVERSITY PROCESS OPTIMISATION Christos Kontzinos, Vagelis Karakolis, Stavros Skalidakis, Ourania Markaki, Maro Androutsopoulou, John Psarras

The aim of Higher Education is twofold: meet the learning needs of individuals through the development of their intellectual abilities, as well as equip them with the necessary skills that will help them enter the labor market. As such, university processes and curricula should be well structured with courses and activities that help students follow their aptitudes, while also providing them with the required level of expertise that the respective job market requires. This paper presents work from the EU funded research project QualiChain that aims to revolutionize the domains of public and private education as well as their connections with the labor market and society at large through the development of a platform that is based on innovative approaches and technologies, such as blockchain, semantics, data analytics and decision support. To achieve its goals regarding education and the labor market , QualiChain involves a pilot targeting student accreditation, curriculum design and process optimization within the School of Electrical & Computer Engineering (ECE) of the National Technical University of Athens (NTUA), which will be the main focus of the present paper.

Ning Zhang, Miguel Baptista Nunes, Guochao Peng, Lijun Wang

Despite its tremendous success, the Chinese Economy is still characterized and controlled by a recurring process of 5 year planning. This comprehensive National planning program occurs at all levels of the Chinese government, educational system and state owned companies. This paper reports on a study that was made in preparation for the 13 th 5 year Plan for the Smart City component of the upcoming city of Tianjin. The objective of this study was to identify problems in i nformatization, automation and centralization of command and control, so that these could be solved as part of the 5 year plan. The study followed a three-stage mixed -method approach. First, questionnaires were used to assess t he sate of development of the smart city fe atures in the different depar tments of the city government. Second, the study organized thematic joint development groups consisting of expert representatives from different city’s departments and units. Third, results of questionnaires and thematic joint development discussions were analyzed in departmental focus groups to clarify and specify the problems and assess proposed solutions and viability of those solutions. This paper analyses the findings of this three-stage process and offers a classification of the identified problems, an integrative conceptual representation of these and a discussion of the importance of this identification in the overall planning process. The results and discussion are of particular importance in China for the next round of 5 year planning that will take place in 2020. However the meaning of the findings of this applied research process are transferable to any smart city planning process all over the world as the majority of the issues discussed are generic.

Wen-Chieh Tung, Jing-Sin Liu

Coverage path planning (CPP) is a fundamental task that is conducted in many applications for machining, cleaning, mine sweeping, lawn mowing, and performing missions by using unmanned aerial vehicles such as mapping, surveillance, search and rescue, and air -quality monitoring. An approach for conducting CPP for a known environment with obstacles involves decomposing the environment into cells such that each cell can be covered individually. The visiting order of the cells can then be decided to connect those intr acell paths together. Finding the shortest intercell path that visits every cell and returns to the origin cell is similar to the traveling salesman problem (TSP). However, an additional variation from TSP that should be considered is that there are multiple intracell paths for each cell. These paths result from different selections of entry and exit points in each cell and thus affect the intercell path. This integrated TSP and CPP problem is known as TSP -CPP and is similar to the TSP with neighborhoods (TSPN). To solve TSP -CPP, one must simultaneously determine the visiting order of sites with minimal repetition and the transition points of each visiting site . The current approaches for solving TSP-CPP are as follows: (i) adapting dynamic programming (DP) for TSP to TSP-CPP, which is excellent for obtaining the optimal route and (ii) determining the optimal route by conducting a brute force enumerative search on entry and exit point combinations for every cell and then solving each combination of entry and exit points with a TSP solver. For large numbers of cells, approaches (i) and (ii) both suffer from exponential complexity and are impractical for complex environments. In this study, we proposed a n appropriate genetic algorithm implementation for TSP -CPP to achieve an optimal balance between time efficiency and path optimality to eliminate the curse of dimensionality in DP. Our approach is demonstrated to find the true optimal solution as DP in all simulation environments that can be solved by both DP and GA, and GA is one hundred times faster than DP approach for maps decomposed with large cell number.

Mohid Tayyub, Gul N. Khan.

Collison detection is a wide -ranging real-world application. It is one of the key components used in gaming, simulation and animation. Efficient algorithms are required for collision detection as it is repeatedly executed throughout the course of an applic ation. Moreover, due to its computationally intensive nature researchers are investigating ways to reduce its execution time. This paper furthers those research works by devising a parallel CPU-GPU implementation of both broad and narrow phase collision detection with heterogenous workload sharing. An important aspect of co-scheduling is to determine an optimal CPU-GPU partition ratio. We also showcase a successive approximation approach for CPU-GPU implementation of collision detection. The paper demonstrates that the framework is not only applicable to CPU/GPU systems but to other system configuration obtaining a peak performance improvement in the range of 18%.

Pedro Isaías

Editorial preface for Volume 14, Issue 2 of the IADIS International Journal on Computer Science and Information Systems (IJCSIS). This issue brings together peer-reviewed original research contributions covering the wide spectrum of Information Systems, Artificial Intelligence, Software Engineering, and Digital Transformation.