Semantic Trajectory Analytics and Recommender Systems in Cultural Spaces

Semantic trajectory analytics and personalised recommender systems that enhance user experience are modern research topics that are increasingly getting attention. Semantic trajectories can efficiently model human movement for further analysis and pattern recognition, while personalised recommender systems can adapt to constantly changing user needs and provide meaningful and optimised suggestions. This paper focuses on the investigation of open issues and challenges at the intersection of these two topics, emphasising semantic technologies and machine learning techniques. The goal of this paper is twofold: (a) to critically review related work on semantic trajectories and knowledge-based interactive recommender systems, and (b) to propose a high-level framework, by describing its requirements. The paper presents a system architecture design for the recognition of semantic trajectory patterns and for the inferencing of possible synthesis of visitor trajectories in cultural spaces, such as museums, making suggestions for new trajectories that optimise cultural experiences.

The EU-SENSE System for Chemical Hazards Detection, Identification, and Monitoring

Chemical reconnaissance, defined as hazards detection, identification, and monitoring, requires tools and solutions which provide reliable and precise data. In this field, the advances of artificial intelligence can be applied. This article aims to propose a novel approach for developing a chemical reconnaissance system that relies on machine learning, modelling algorithms, as well as the contaminant dispersion model to combine signals from different sensors and reduce false alarm rates. A case study of the European Union Horizon 2020 project–EU-SENSE is used and the main features of the system are analysed: heterogeneous sensor nodes components, chemical agents to be detected, and system architecture design. Through the proposed approach, chemical reconnaissance capabilities are improved, resulting in more effective crisis management. The idea for the system design can be used and developed in other areas, namely, in biological or radiological threat reconnaissance.

Research on the Design of Mass Recommendation System Based on Lambda Architecture

In the era of big data, in order to increasing the information data for conforms to the personalized needs of content, research scholars put forward based on the Lambda mass recommendation system architecture design, it can not only to the recessive and dominant behavior of users of the system data collection storage and research analysis, can also be based on the analysis of cascading hybrid algorithm to explore how to carry out real-time recommendation. Therefore, on the basis of understanding the research and development achievements of recommender systems at home and abroad in recent years, and based on the understanding and analysis of Lambda architecture and cascading hybrid algorithm, this paper aims at how to design a massive recommender system in line with users’ behavior, and makes clear the recommendation effect by combining with system testing.

Modeling the Effects of Machine Rigidities on Joint Work Strategies

One of the challenges in designing resilient human-machine systems is that machine capabilities are inherently rigid. A resilient joint cognitive system can anticipate and adapt to changing work demands effectively, but limitations of machines can make this adaptation constrained and less fluid. By identifying and accommodating for these rigidities in the design of human-machine system architectures, developers can build human-machine systems that support multiple contexts. This paper proposes a work-modeling approach for analyzing joint human-machine work strategies, focusing on identifying interdependencies that would support opportunistic adaptation and reduce the risk of machine rigidity leading to brittle failures of a human-machine system. The approach is applied to a case study in space operations to demonstrate how interdependencies can be identified and evaluated. The results of this analysis provide early insight into how team adaptation and machine limitations can be systematically accounted for in system architecture design.

RESOLUTION OF SAFETY RELEVANT SECURITY THREATS IN THE SYSTEM ARCHITECTURE DESIGN PHASE ON THE EXAMPLE OF AUTOMOTIVE INDUSTRY

Cyber-physical systems (CPS), like autonomous vehicles, are intelligent and networked. The development of such systems and its components requires interdisciplinary cooperation between different stakeholders. A lack of system understanding between stakeholders can lead to unidentified and unresolved security threats & safety hazards in early engineering phases, resulting in high costs in product development and potentially compromises compliance with the safety of CPS.Model-based systems engineering (MBSE) improves the system understanding between stakeholders by using models.However, MBSE approaches only partially address security threats & safety hazards. In particular, their integrative consideration is not taken into account.Established security & safety approaches are either only applicable to specific disciplines or only partially consider security threats & safety hazards.In the context of this paper we present a method for the resolution of safety relevant security threats in the system architecture design phase using design patterns.We illustrate our approach with the example of the automotive sector.Finally, we present an evaluation of the method, based on an 8 week project with 67 master students.

Designing An Application of Software Project Management By Using Framework Scrum (SPM-Scrum)

Most of failures of startup application in many countries reached 75%, while the startup failures in Indonesia reached 90%. These failures were caused by non-technical or management factors in managing startup. The RPL (Software Engineering) Laboratory of FILKOM of Brawijaya University has a roadmap to develop an application to guarantee the success of a management software project. The data analysis had been performed on FILKOM student’s thesis work which generally develops software that has main obstacle in the management. A study solution which was developed through scientific SDLC and PMLC combined with Scrum method becomes an application named SPM-SCRUM. The results of analysis carried out on several software development projects refer to the Iterative SDPM process. Furthermore, the strategy of Iterative SDPM combined with Scrum method produces a system architecture design that separates the Front End and Back End